Word2vec

word2vec.ipynb

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    "Word2vec from Manaus\n",
    "=============\n",
    "\n",
    "Taken from [Udacity Course](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/udacity/5_word2vec.ipynb) assignment 5.\n",
    "\n",
    "What it does\n",
    "------------\n",
    "\n",
    "Accept list of lists of keyword and predict the similarity of keywords according to their companions.\n",
    "\n",
    "GPU or CPU?\n",
    "----------\n",
    "\n",
    "Unless you have NVidia, it's CPU because Tensorflow does not support OpenCL. At the moment it does not work with [tf-coriander](https://github.com/hughperkins/tf-coriander).\n"
   ]
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   "source": [
    "# These are all the modules we'll be using later. Make sure you can import them\n",
    "# before proceeding further.\n",
    "from __future__ import print_function\n",
    "from __future__ import division\n",
    "import itertools\n",
    "import collections\n",
    "import math\n",
    "import numpy as np\n",
    "from scipy.spatial.distance import cosine\n",
    "import os\n",
    "import random\n",
    "import tensorflow as tf\n",
    "import re\n",
    "# import zipfile\n",
    "from matplotlib import pylab\n",
    "from six.moves import range\n",
    "from six.moves.urllib.request import urlretrieve\n",
    "from sklearn.manifold import TSNE\n"
   ]
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   "cell_type": "markdown",
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    "id": "aCjPJE944bkV"
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   "source": [
    "Download the data from the source website if necessary."
   ]
  },
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    "outputId": "c4ec222c-80b5-4298-e635-93ca9f79c3b7"
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   "outputs": [],
   "source": [
    "filename = 'keywords.fsecure.tsv'"
   ]
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   "outputs": [
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     "name": "stdout",
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     "text": [
      "Data size 105185\n"
     ]
    }
   ],
   "source": [
    "def read_data(filename):\n",
    "    \"\"\"Extract all words all alpha and not uppercase\n",
    "    words: list of all words\n",
    "    sentences: list of lists, each list a sentence\n",
    "    sentences_index: list, each element how to find that word in sentences: (4,3) word 3 in sentence 4\n",
    "    \"\"\"\n",
    "    # list of list of words\n",
    "    sentences = list()\n",
    "    # all words in order of apparence (repeated)\n",
    "    words = list()\n",
    "    # (sentence_index_in_sentences, word_index_in_sentence) => index in words\n",
    "    sentences_index_dict = dict()\n",
    "    # index in words => (sentence_index_in_sentences, word_index_in_sentence)\n",
    "    sentences_index = []\n",
    "    with open(filename) as f:\n",
    "        sentence_count = 0\n",
    "        for line in f.readlines():\n",
    "            sentence = list()\n",
    "            word_count = 0\n",
    "            for word in line.replace('\"', ' ').replace('|', ' ').replace('\";\"', ' ').split():\n",
    "                if word.isalpha() and not word.isupper():\n",
    "                    #print(word)\n",
    "                    words.append(word)\n",
    "                    sentence.append(word)\n",
    "                    sentences_index_dict[(sentence_count, word_count)] = len(words) - 1\n",
    "                    sentences_index.append((sentence_count, word_count))\n",
    "                    word_count += 1\n",
    "            sentences.append(sentence)\n",
    "            sentence_count += 1\n",
    "                \n",
    "    return words, sentences, sentences_index, sentences_index_dict\n",
    "  \n",
    "words, sentences, sentences_index, sentences_index_dict = read_data(filename)\n",
    "print('Data size %d' % len(words))"
   ]
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   "execution_count": 4,
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     "text": [
      "['jacob', 'validation', 'imac', 'aware', 'ios', 'activation', 'activated', 'currently', 'installing']\n",
      "[['jacob', 'validation', 'imac', 'aware', 'ios', 'activation', 'activated', 'currently', 'installing', 'mac', 'reset', 'app', 'device', 'devices'], ['wild', 'wed', 'exede', 'assure', 'directed', 'immediately', 'web', 'site'], ['charlie', 'anywhere', 'applet', 'clicked'], ['trial', 'expired', 'code', 'subscription', 'install'], ['unsure', 'false', 'showed', 'response', 'details', 'freedome']]\n",
      "[(0, 0), (0, 1), (0, 2), (0, 3), (0, 4), (0, 5), (0, 6), (0, 7)]\n",
      "0\n"
     ]
    }
   ],
   "source": [
    "print(words[:9])\n",
    "print(sentences[:5])\n",
    "print(sentences_index[:8])\n",
    "print(sentences_index_dict[(0, 0)])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   },
   "source": [
    "#### Add possible synonyms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
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   "source": [
    "# Libraries for Lev distance\n",
    "def _edit_dist_init(len1, len2):\n",
    "    lev = []\n",
    "    for i in range(len1):\n",
    "        lev.append([0] * len2)  # initialize 2D array to zero\n",
    "    for i in range(len1):\n",
    "        lev[i][0] = i           # column 0: 0,1,2,3,4,...\n",
    "    for j in range(len2):\n",
    "        lev[0][j] = j           # row 0: 0,1,2,3,4,...\n",
    "    return lev\n",
    "\n",
    "\n",
    "def _edit_dist_step(lev, i, j, s1, s2, substitution_cost=1, transpositions=False):\n",
    "    c1 = s1[i - 1]\n",
    "    c2 = s2[j - 1]\n",
    "\n",
    "    # skipping a character in s1\n",
    "    a = lev[i - 1][j] + 1\n",
    "    # skipping a character in s2\n",
    "    b = lev[i][j - 1] + 1\n",
    "    # substitution\n",
    "    c = lev[i - 1][j - 1] + (substitution_cost if c1 != c2 else 0)\n",
    "\n",
    "    # transposition\n",
    "    d = c + 1  # never picked by default\n",
    "    if transpositions and i > 1 and j > 1:\n",
    "        if s1[i - 2] == c2 and s2[j - 2] == c1:\n",
    "            d = lev[i - 2][j - 2] + 1\n",
    "\n",
    "    # pick the cheapest\n",
    "    lev[i][j] = min(a, b, c, d)\n",
    "\n",
    "\n",
    "def edit_distance(s1, s2, substitution_cost=1, transpositions=False):\n",
    "    \"\"\"\n",
    "    Calculate the Levenshtein edit-distance between two strings.\n",
    "    The edit distance is the number of characters that need to be\n",
    "    substituted, inserted, or deleted, to transform s1 into s2.  For\n",
    "    example, transforming \"rain\" to \"shine\" requires three steps,\n",
    "    consisting of two substitutions and one insertion:\n",
    "    \"rain\" -> \"sain\" -> \"shin\" -> \"shine\".  These operations could have\n",
    "    been done in other orders, but at least three steps are needed.\n",
    "\n",
    "    Allows specifying the cost of substitution edits (e.g., \"a\" -> \"b\"),\n",
    "    because sometimes it makes sense to assign greater penalties to substitutions.\n",
    "\n",
    "    This also optionally allows transposition edits (e.g., \"ab\" -> \"ba\"),\n",
    "    though this is disabled by default.\n",
    "\n",
    "    :param s1, s2: The strings to be analysed\n",
    "    :param transpositions: Whether to allow transposition edits\n",
    "    :type s1: str\n",
    "    :type s2: str\n",
    "    :type substitution_cost: int\n",
    "    :type transpositions: bool\n",
    "    :rtype int\n",
    "    \"\"\"\n",
    "    # set up a 2-D array\n",
    "    len1 = len(s1)\n",
    "    len2 = len(s2)\n",
    "    lev = _edit_dist_init(len1 + 1, len2 + 1)\n",
    "\n",
    "    # iterate over the array\n",
    "    for i in range(len1):\n",
    "        for j in range(len2):\n",
    "            _edit_dist_step(lev, i + 1, j + 1, s1, s2,\n",
    "                            substitution_cost=substitution_cost, transpositions=transpositions)\n",
    "    return lev[len1][len2]\n",
    "\n",
    "def jaccard_distance(label1, label2):\n",
    "    \"\"\"Distance metric comparing set-similarity.\n",
    "\n",
    "    \"\"\"\n",
    "    return (len(label1.union(label2)) - len(label1.intersection(label2)))/len(label1.union(label2))\n",
    "\n",
    "def masi_distance(label1, label2):\n",
    "    \"\"\"Distance metric that takes into account partial agreement when multiple\n",
    "    labels are assigned.\n",
    "\n",
    "    >>> from nltk.metrics import masi_distance\n",
    "    >>> masi_distance(set([1, 2]), set([1, 2, 3, 4]))\n",
    "    0.335\n",
    "\n",
    "    Passonneau 2006, Measuring Agreement on Set-Valued Items (MASI)\n",
    "    for Semantic and Pragmatic Annotation.\n",
    "    \"\"\"\n",
    "\n",
    "    len_intersection = len(label1.intersection(label2))\n",
    "    len_union = len(label1.union(label2))\n",
    "    len_label1 = len(label1)\n",
    "    len_label2 = len(label2)\n",
    "    if len_label1 == len_label2 and len_label1 == len_intersection:\n",
    "        m = 1\n",
    "    elif len_intersection == min(len_label1, len_label2):\n",
    "        m = 0.67\n",
    "    elif len_intersection > 0:\n",
    "        m = 0.33\n",
    "    else:\n",
    "        m = 0\n",
    "\n",
    "    return (1 - (len_intersection / float(len_union))) * m\n",
    "\n",
    "\n",
    "\n",
    "def interval_distance(label1,label2):\n",
    "    \"\"\"Krippendorff's interval distance metric\n",
    "\n",
    "    >>> from nltk.metrics import interval_distance\n",
    "    >>> interval_distance(1,10)\n",
    "    81\n",
    "\n",
    "    Krippendorff 1980, Content Analysis: An Introduction to its Methodology\n",
    "    \"\"\"\n",
    "\n",
    "    try:\n",
    "        return pow(label1 - label2, 2)\n",
    "#        return pow(list(label1)[0]-list(label2)[0],2)\n",
    "    except:\n",
    "        print(\"non-numeric labels not supported with interval distance\")\n",
    "\n",
    "\n",
    "\n",
    "def presence(label):\n",
    "    \"\"\"Higher-order function to test presence of a given label\n",
    "    \"\"\"\n",
    "\n",
    "    return lambda x, y: 1.0 * ((label in x) == (label in y))\n",
    "\n",
    "\n",
    "\n",
    "def fractional_presence(label):\n",
    "    return lambda x, y:\\\n",
    "        abs(((1.0 / len(x)) - (1.0 / len(y)))) * (label in x and label in y) \\\n",
    "        or 0.0 * (label not in x and label not in y) \\\n",
    "        or abs((1.0 / len(x))) * (label in x and label not in y) \\\n",
    "        or ((1.0 / len(y))) * (label not in x and label in y)\n",
    "\n",
    "\n",
    "\n",
    "def custom_distance(file):\n",
    "    data = {}\n",
    "    with open(file, 'r') as infile:\n",
    "        for l in infile:\n",
    "            labelA, labelB, dist = l.strip().split(\"\\t\")\n",
    "            labelA = frozenset([labelA])\n",
    "            labelB = frozenset([labelB])\n",
    "            data[frozenset([labelA,labelB])] = float(dist)\n",
    "    return lambda x,y:data[frozenset([x,y])]\n",
    "\n",
    "def binary_distance(label1, label2):\n",
    "    \"\"\"Simple equality test.\n",
    "\n",
    "    0.0 if the labels are identical, 1.0 if they are different.\n",
    "\n",
    "    >>> from nltk.metrics import binary_distance\n",
    "    >>> binary_distance(1,1)\n",
    "    0.0\n",
    "\n",
    "    >>> binary_distance(1,3)\n",
    "    1.0\n",
    "    \"\"\"\n",
    "\n",
    "    return 0.0 if label1 == label2 else 1.0\n",
    "\n",
    "\n",
    "def demo():\n",
    "    edit_distance_examples = [\n",
    "        (\"install\", \"installation\"), (\"abcdef\", \"acbdef\"), (\"implementation\", \"installation\"),\n",
    "        (\"language\", \"lnaugage\"), (\"language\", \"lngauage\")]\n",
    "    for s1, s2 in edit_distance_examples:\n",
    "        print(\"Edit distance between '%s' and '%s':\" % (s1, s2), edit_distance(s1, s2))\n",
    "    for s1, s2 in edit_distance_examples:\n",
    "        print(\"Edit distance with transpositions between '%s' and '%s' with Transpo:\" % (s1, s2), edit_distance(s1, s2, transpositions=True))\n",
    "    for s1, s2 in edit_distance_examples:\n",
    "        print(\"Edit distance with transpositions between '%s' and '%s' NO Transpo:\" % (s1, s2), edit_distance(s1, s2, transpositions=False))\n",
    "    for s1, s2 in edit_distance_examples:\n",
    "        print(\"TRUNCATED Edit distance with transpositions between '%s' and '%s':\" % (s1, s2), edit_distance(s1[4:min(8, len(s1), len(s2))], s2[4:min(8, len(s1), len(s2))]))\n",
    "    for s1, s2 in edit_distance_examples:\n",
    "        print(\"Jaccard distance between '%s' and '%s':\" % (s1, s2), jaccard_distance(set(s1), set(s2)))\n",
    "    for s1, s2 in edit_distance_examples:\n",
    "        print(\"MASI distance between '%s' and '%s':\" % (s1, s2), masi_distance(set(s1), set(s2)))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#demo()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def synonyms_candidates(words):\n",
    "    words = set(words)\n",
    "    syn_sentences = []\n",
    "    while len(words) > 1:\n",
    "        w = words.pop()\n",
    "        sentence = [w]\n",
    "        for w2 in words:\n",
    "            L = min(8, len(w), len(w2))\n",
    "            if w[:4] == w2[:4] and edit_distance(w[4:L], w2[4:L]) < 2:\n",
    "                sentence.append(w2)\n",
    "        words.difference_update(set(sentence))\n",
    "        if len(sentence) > 1:\n",
    "            syn_sentences.append(sentence)\n",
    "    return(syn_sentences)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# sentences += synonyms_candidates(set(words))\n",
    "synonyms = synonyms_candidates(set(words))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[['treetment', 'tree'], ['foud', 'foudn'], ['secondly', 'seconds'], ['instalations', 'install', 'instal', 'instalation', 'installtion', 'instalar'], ['advices', 'advice', 'advise'], ['andre', 'andrus', 'andrew', 'andrea', 'andreas', 'android', 'andrej', 'andriod'], ['internert', 'interfering', 'internetsecurity', 'interner', 'internet', 'internett', 'inter', 'interfere'], ['hanging', 'hang', 'hangs'], ['gabriella', 'gabrielle'], ['fredrik', 'fred', 'freda'], ['unblocked', 'unblock'], ['intro', 'intrusion', 'intrusive', 'introduced', 'introduce'], ['visable', 'visa'], ['contained', 'containing', 'cont', 'contd', 'contains', 'contain'], ['differend', 'differently', 'differant', 'differance', 'differ', 'difference', 'differences'], ['refunding', 'refunds', 'refund'], ['swap', 'swapping', 'swapped'], ['offending', 'offer'], ['digit', 'digital', 'digits'], ['activation', 'activating', 'active', 'activated', 'activ', 'activations', 'activate', 'activationcode'], ['kaspersky', 'kasper'], ['raymondcustomer', 'raymond'], ['malfunctioned', 'malfunction'], ['affect', 'affecting', 'affected'], ['basics', 'basis', 'basic', 'basically'], ['reformatted', 'reformat'], ['companies', 'company', 'comp'], ['charter', 'charle', 'charge'], ['force', 'forced', 'forces'], ['specially', 'specialist', 'special'], ['warns', 'warn', 'warned', 'warnings', 'warning'], ['likely', 'liked'], ['available', 'avail', 'availability'], ['melvin', 'melvyn'], ['theory', 'theo'], ['errors', 'error', 'errormessage'], ['preferences', 'prefer'], ['integrity', 'integrated'], ['fingers', 'finger', 'fingerprint'], ['lights', 'lighter', 'light'], ['probelm', 'probs', 'prob'], ['poorly', 'poor'], ['interrupting', 'interrupted', 'interrupt'], ['reported', 'reports', 'report'], ['china', 'chinthaka', 'chinese'], ['hers', 'herself'], ['cardboard', 'card', 'cards'], ['covers', 'coverd', 'cover', 'coverage', 'covering', 'covered'], ['reactivated', 'reactivate', 'reactive', 'reach'], ['reinstallation', 'reino', 'reinstal', 'reinstalled', 'reinstated', 'reinstall', 'reinstalling', 'reinstate'], ['credit', 'cred', 'creditcard', 'credited'], ['karin', 'karien', 'kari'], ['pack', 'package', 'packag', 'packet', 'packed', 'packard', 'packages', 'packaging', 'packs'], ['cancellation', 'cancelled', 'cancel', 'cancell', 'cancelling'], ['remotly', 'remote', 'remot'], ['joshua', 'josh'], ['unin', 'uninstalling', 'uninstallation', 'unintentionally', 'uninstaller', 'uninstalled', 'uninstal', 'uninstall', 'uninstalls'], ['campaign', 'camp', 'campain'], ['explained', 'explain', 'explaining', 'explaination', 'explaind', 'explains'], ['lynne', 'lynn'], ['automated', 'automaticly', 'automatical', 'automatic', 'automatically', 'auto'], ['costas', 'costs', 'cost'], ['janine', 'jani', 'janis', 'janice'], ['counts', 'country', 'counter', 'counted', 'countries', 'count', 'counting'], ['unit', 'unitool', 'unitoool', 'united', 'units'], ['spoke', 'spoken'], ['browse', 'browsers', 'browsing', 'browser', 'brown'], ['remenber', 'remembering', 'remembered'], ['grahame', 'graham'], ['diederik', 'died'], ['emailaddress', 'emailadress', 'emailed', 'emailadres', 'emai', 'email', 'emails'], ['therefore', 'therefor', 'theres', 'ther'], ['recommend', 'recommended', 'recommendations', 'recommendation'], ['reconnection', 'reconnected', 'reconnect', 'reconnecting'], ['type', 'typed', 'types', 'typer'], ['barry', 'barrie'], ['expiring', 'expiry', 'expire'], ['paperwork', 'paper', 'papers'], ['posting', 'post', 'posts'], ['relay', 'relax', 'relaunch', 'relating', 'related', 'relatively', 'relation', 'relates'], ['successful', 'success', 'successfull', 'successfully'], ['expose', 'exposed'], ['hereby', 'heres'], ['ware', 'warehouse'], ['locked', 'locks', 'lock'], ['organized', 'organization'], ['updated', 'updates', 'update'], ['currency', 'current'], ['bluescreen', 'blue'], ['mail', 'mailing', 'mailaddress', 'mailadress', 'mails', 'mailbox', 'mailed'], ['appearance', 'appearing', 'appear', 'appears'], ['preferably', 'preferable'], ['satu', 'saturday'], ['complaining', 'complaint', 'complain', 'complaints', 'compra', 'complained', 'complains'], ['travel', 'travelling', 'traveling'], ['damage', 'damaged'], ['machine', 'machines', 'mach'], ['mite', 'miten'], ['faulty', 'fault'], ['ronnie', 'ronny']]\n"
     ]
    }
   ],
   "source": [
    "print(synonyms[:100])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Zdw6i4F8glpp"
   },
   "source": [
    "#### Build the dictionary variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "cellView": "both",
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     "autoexec": {
      "startup": false,
      "wait_interval": 0
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     "output_extras": [
      {
       "item_id": 1
      }
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    },
    "colab_type": "code",
    "collapsed": false,
    "executionInfo": {
     "elapsed": 28849,
     "status": "ok",
     "timestamp": 1445964497178,
     "user": {
      "color": "#1FA15D",
      "displayName": "Vincent Vanhoucke",
      "isAnonymous": false,
      "isMe": true,
      "permissionId": "05076109866853157986",
      "photoUrl": "//lh6.googleusercontent.com/-cCJa7dTDcgQ/AAAAAAAAAAI/AAAAAAAACgw/r2EZ_8oYer4/s50-c-k-no/photo.jpg",
      "sessionId": "2f1ffade4c9f20de",
      "userId": "102167687554210253930"
     },
     "user_tz": 420
    },
    "id": "gAL1EECXeZsD",
    "outputId": "3fb4ecd1-df67-44b6-a2dc-2291730970b2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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('wxgz', 1), ('srivellus', 1), ('someting', 1), ('restrict', 1), ('tor', 1), ('bitcoin', 1), ('illiterate', 1), ('refernce', 1), ('deinstallation', 1), ('faustina', 1), ('baupr', 1), ('rohit', 1), ('ohhhh', 1), ('adminstrator', 1), ('brandon', 1), ('sethy', 1), ('safevip', 1), ('qguhn', 1), ('pkv', 1), ('ransomware', 1), ('claude', 1), ('beacause', 1), ('goona', 1), ('catalin', 1), ('translating', 1), ('mahmoud', 1), ('sadegh', 1), ('zbm', 1), ('aquarius', 1), ('phoning', 1), ('wear', 1), ('vanden', 1), ('elm', 1), ('interent', 1), ('hiagent', 1), ('experts', 1), ('complex', 1), ('complet', 1), ('encrypts', 1), ('josmaarten', 1), ('eli', 1), ('dearer', 1), ('ele', 1), ('apears', 1), ('tring', 1), ('anthon', 1), ('jya', 1), ('gxqyj', 1), ('sanjay', 1), ('plum', 1), ('bodil', 1), ('git', 1), ('posession', 1), ('anderson', 1), ('krispijn', 1), ('differences', 1), ('wireless', 1), ('neva', 1), ('trip', 1), ('chech', 1), ('tit', 1), ('borre', 1), ('corresponding', 1), ('rom', 1), ('valentin', 1), ('standards', 1), ('sercure', 1), ('cyril', 1), ('mumbai', 1), ('shelley', 1), ('crisis', 1), ('reactive', 1), ('symantec', 1), ('referense', 1), ('dropped', 1), ('alway', 1), ('hihi', 1), ('mounths', 1), ('gta', 1), ('hanks', 1), ('individually', 1), ('farewell', 1), ('cancell', 1), ('allways', 1), ('nned', 1), ('yur', 1), ('yuo', 1), ('rosca', 1), ('legally', 1), ('serv', 1), ('wide', 1), ('evertime', 1), ('uese', 1), ('havnt', 1), ('ane', 1), ('anf', 1), ('prb', 1), ('prk', 1), ('ank', 1), ('prv', 1), ('kush', 1), ('chahna', 1), ('tena', 1), ('tke', 1), ('spaces', 1), ('farzana', 1), ('leigh', 1), ('secirity', 1), ('ssd', 1), ('mapper', 1), ('viaplay', 1), ('noreen', 1), ('jindrich', 1), ('outside', 1), ('tania', 1), ('uptodate', 1), ('por', 1), ('kev', 1), ('hardly', 1), ('andrej', 1), ('premature', 1), ('cast', 1), ('vesa', 1), ('acess', 1), ('ecbp', 1), ('granted', 1), ('hebben', 1), ('relief', 1), ('norhing', 1), ('halfway', 1), ('ross', 1), ('packaging', 1), ('silverlight', 1), ('madrid', 1), ('redeeming', 1), ('frees', 1), ('stopt', 1), ('elegal', 1), ('jswr', 1), ('foreward', 1), ('ehm', 1), ('jun', 1), ('applying', 1), ('adsl', 1), ('idiot', 1), ('proseed', 1), ('releasing', 1), ('stocks', 1), ('mwxen', 1), ('alb', 1), ('abit', 1), ('progran', 1), ('ftk', 1), ('sevure', 1), ('befofre', 1), ('ten', 1), ('reino', 1), ('stancustomer', 1), ('whan', 1), ('lzra', 1), ('ntlworld', 1), ('maby', 1), ('texts', 1), ('thays', 1), ('dwade', 1), ('israel', 1), ('qdhe', 1), ('operators', 1), ('mira', 1), ('pone', 1), ('court', 1), ('speeding', 1), ('zzqe', 1), ('shore', 1), ('installtion', 1), ('alrite', 1), ('style', 1), ('soccer', 1), ('prodcut', 1), ('downlode', 1), ('gotab', 1), ('comfirm', 1), ('mastercard', 1), ('enandcurrency', 1), ('hartley', 1), ('health', 1), ('forgive', 1), ('lag', 1), ('throws', 1), ('passes', 1), ('confurm', 1), ('relieved', 1), ('hotel', 1), ('remot', 1), ('aimo', 1), ('stall', 1), ('fidellis', 1), ('saya', 1), ('basel', 1), ('donot', 1), ('flemming', 1), ('cde', 1), ('aernout', 1), ('luis', 1), ('alicia', 1), ('hii', 1), ('sofie', 1), ('mcustomer', 1), ('ssafe', 1), ('finde', 1), ('duh', 1), ('decline', 1), ('todate', 1), ('ahau', 1), ('zrce', 1), ('chouaib', 1), ('qgqc', 1), ('subscriotion', 1), ('arthur', 1), ('campagne', 1), ('czv', 1), ('jimmie', 1), ('mutta', 1), ('mikhail', 1), ('regiister', 1), ('itout', 1), ('ands', 1), ('vbqmj', 1), ('tone', 1), ('suomalainen', 1), ('annemarie', 1), ('mcdonnell', 1), ('dale', 1), ('yopu', 1), ('vigin', 1), ('problema', 1), ('rmyz', 1), ('makelberge', 1), ('jorgen', 1), ('licnese', 1), ('cuppa', 1), ('stable', 1), ('relation', 1), ('carollyn', 1), ('kiitos', 1), ('englanniksi', 1), ('capital', 1), ('deraldo', 1), ('olivier', 1), ('apt', 1), ('webmail', 1), ('gerd', 1), ('eleazar', 1), ('pyaqs', 1), ('bleyen', 1), ('wvffv', 1), ('kyed', 1), ('securen', 1), ('light', 1), ('synology', 1), ('janti', 1), ('promptly', 1), ('appy', 1), ('lte', 1), ('instalar', 1), ('mgnoe', 1), ('egill', 1), ('beter', 1), ('rememeber', 1), ('clic', 1), ('cdkeys', 1), ('krista', 1), ('whick', 1), ('fujitsu', 1), ('diagnostics', 1), ('purely', 1), ('brain', 1), ('bluetooth', 1), ('favor', 1), ('iot', 1), ('tiina', 1), ('asnnk', 1), ('alyn', 1), ('observ', 1), ('offending', 1), ('anju', 1), ('cogeco', 1), ('nessecary', 1), ('idris', 1), ('albin', 1), ('theses', 1), ('gutted', 1), ('elleson', 1), ('fishing', 1), ('expedite', 1), ('dqj', 1), ('enheder', 1), ('referal', 1), ('execute', 1), ('nedd', 1), ('ehgt', 1), ('ahed', 1), ('ppdr', 1), ('xoygn', 1), ('mozila', 1), ('lead', 1), ('apostolis', 1), ('mite', 1), ('matshita', 1), ('maisa', 1), ('uninstalls', 1), ('vas', 1), ('shane', 1), ('jepp', 1), ('anja', 1), ('jenny', 1), ('incredible', 1), ('corrrect', 1)]\n",
      "Sample data [[4307, 6166], [4308, 4711], [2667, 2349], [4309, 2, 748, 1468, 7471, 7561], [4310, 636, 349], [1882, 3932, 228, 4177, 1276, 95, 7416, 4266], [6119, 2481, 3490, 6248, 3, 2927, 3519, 3825], [4311, 3312, 2823], [6120, 1799], [3843, 1615, 6700], [6121, 1696], [5893, 2490, 4012, 4077, 4906], [6895, 976], [1477, 2774, 4824, 5747, 1218, 1873], [5428, 3862, 6960, 7126, 4556, 495, 7352], [3438, 3947, 138], [3845, 5030, 5707], [7581, 223], [772, 1166, 1755], [205, 774, 97, 183, 6265, 5472, 57, 6797], [884, 2290], [4335, 486], [6125, 1127], [1036, 3509, 1457], [6127, 2682, 1102, 531], [3439, 2865], [1395, 810, 1058], [2199, 6304, 567], [2090, 2580, 3668], [4315, 4318, 4084], [5224, 5235, 4040, 3388, 441], [1099, 1863], [114, 1537, 5736], [2871, 3282], [5830, 7071], [773, 46, 4640], [3850, 585], [5225, 3296], [1978, 2392, 4267], [6899, 5852, 7555], [6900, 2099, 2451], [4085, 1860], [6131, 6030, 2930], [919, 1195, 566], [1979, 3179, 5899], [2473, 6836], [2489, 101, 1624], [944, 5333, 211, 1469, 4806, 144], [6132, 977, 7368, 1007], [942, 7453, 3563, 203, 4658, 31, 526, 2838], [251, 5245, 3224, 5763], [1531, 3748, 1296], [863, 160, 4568, 3625, 6462, 4738, 1458, 7428, 5070], [1642, 412, 120, 7379, 1785], [4319, 96, 7490], [2322, 4842], [6133, 502, 1388, 4416, 1269, 133, 1753, 50, 7607], [242, 6173, 1823], [920, 1398, 2360, 6483, 5930, 2171], [2873, 656], [3436, 2325, 4664, 423, 210, 505], [2794, 1649, 322], [3853, 1802, 2506, 1961], [3166, 1139, 2546, 6425, 4111, 3023, 2404], [1261, 4588, 3781, 3414, 771], [535, 1143], [2474, 992, 338, 109, 6596], [6907, 4374, 3255], [3440, 462], [2324, 5337], [2475, 3183, 1042, 4462, 2531, 1, 134], [407, 4666, 1008, 1083], [492, 716, 3768, 5670], [4324, 4793, 2432, 6085], [272, 747, 2877, 6147], [706, 6668], [623, 365, 132], [1980, 3551, 5775], [6912, 1028, 3343], [6138, 6139, 5894, 3483, 622, 6375, 7539, 3420], [746, 727, 7192, 383], [6913, 6665], [6140, 7010], [1478, 5335], [417, 2904, 485], [6142, 6172], [172, 149, 39], [2477, 82], [6143, 1000], [23, 2989, 2792, 7188, 410, 3247, 4299], [5659, 1514, 274, 184], [3441, 6145], [6917, 1759], [2478, 845, 2117, 2109, 7222, 2616, 3892], [2479, 4542, 2844], [1643, 1801], [104, 227, 6741], [7604, 6714], [1716, 2772], [6146, 1604], [3495, 3424, 1610, 5111, 993], [5240, 5688], [3859, 687, 226], [3860, 2043], [3443, 2248, 2850], [7335, 2594, 5805, 3815], [310, 1594, 7025, 6563], [788, 1334, 1756], [43, 5488, 1111, 37, 2545, 648], [675, 1101, 1928, 1055], [2202, 3446, 869], [728, 1926], [3861, 6922, 5550, 4722, 1158, 3122, 372], [5242, 3889, 5829, 2778, 308], [3168, 273], [1107, 4401], [700, 5915], [164, 2235], [3847, 1722, 155, 3766], [2326, 6073, 1365, 3607, 708, 3740, 7464, 5168, 1420], [1981, 5567, 218, 7, 2469], [5832, 5295, 665, 216, 5176], [715, 5954], [2385, 2124], [6149, 3238, 87, 2406, 3987, 7554, 1340], [4336, 4684, 835, 3833, 1304], [3169, 943], [5303, 560], [789, 6980, 7181, 3184, 5870], [3864, 1699], [584, 1806], [5247, 5807, 2559], [1800, 289], [5249, 21, 5559, 865, 1975], [3866, 7374], [3867, 222, 906, 0, 3975, 3538, 3559, 5569, 1169, 4118, 5578, 545, 2802, 1039, 7514, 847], [2094, 2898], [6925, 58, 5251, 6927, 767, 3844, 1332, 25, 2817, 3802], [1396, 1837, 2849], [4340, 2080], [2178, 3838], [3172, 2174], [905, 5911, 340], [2879, 1302], [1066, 3553], [392, 809, 15], [4510, 2586, 3674], [1067, 2098, 6492, 4867, 4158, 4159, 3809], [6311, 3874], [2049, 4365, 2816], [5252, 4799, 3046], [2881, 1081, 4572, 6485, 1210, 500, 5204, 3160], [988, 6542, 5979, 5214], [5253, 5601], [6931, 280, 1902, 3622, 819, 4868], [1718, 1563], [6156, 5115], [2882, 900, 342, 1499], [960, 4715, 1676, 894, 7266, 6849], [234, 1511], [6157, 962, 7612], [3871, 3214], [4086, 2273], [369, 3660, 2293], [989, 872, 2015, 1881], [238, 5323, 6685, 2388, 93], [4343, 6655], [1984, 2482, 7468, 630], [2951, 2484, 642, 2952, 4541, 5084], [1197, 2238, 5591, 83], [6163, 1669], [370, 625], [3174, 5321], [4344, 4353, 1017, 108, 663, 6019], [3873, 4354, 7250, 710, 2685], [3449, 5343], [118, 422, 4100, 7386], [1519, 1020, 2708, 600], [966, 3988], [1262, 7479], [319, 4968, 356, 2308], [5258, 5298, 2573], [7039, 619, 3392], [5259, 249], [3452, 2029], [874, 3481, 2517], [5262, 561], [6938, 2609, 794, 2756], [1309, 6939], [5263, 4043], [570, 537, 102], [5265, 5375], [633, 2257], [3875, 1606], [2830, 5161], [1310, 2793, 5872, 5145, 3830], [1985, 6083, 1314, 5401], [3877, 4182, 557], [3175, 245, 2336, 733, 2911, 3376, 3264, 6454, 1116, 260, 1399, 7448, 22, 2450, 6110], [7130, 438, 281], [2096, 646], [1887, 2715], [4352, 640, 292, 5495, 4010, 1462], [3176, 4545], [5267, 5925], [5986, 6866], [270, 5077], [7338, 5320], [3879, 652, 653, 3212, 7217, 2033, 4139, 3061, 1131, 5075, 7262, 1222, 2654], [6943, 5396, 723, 2748, 1251, 4164, 1574, 593], [1226, 5905, 5637], [1535, 895], [1741, 4454, 3060], [4357, 2050], [3882, 5878, 6879], [1667, 2908, 3558, 6097, 7239], [465, 2005, 6282, 5598, 3004, 3339, 5774, 553, 2069, 650], [1720, 7191, 6701, 5958], [4361, 2418], [125, 41, 7566], [4140, 6627], [1644, 2288], [1536, 1496, 2116, 3331, 468], [517, 3755], [2486, 3139], [1436, 3456, 178], [2678, 6017], [448, 1603], [3885, 2679, 4390, 806, 432, 2168], [3180, 2113, 1018, 7087, 3221, 2947, 7129, 106, 5962, 7594], [559, 4988, 363, 3807], [3457, 6754], [5277, 4451, 70], [3181, 1858, 241, 5040], [2328, 1734], [4674, 3287], [6175, 7051, 3368, 1442, 6331, 5720, 6687, 258, 1467], [518, 568, 7443], [3458, 5710], [2487, 1886], [2884, 2888], [4363, 1150, 4198], [1165, 1463, 4069], [5227, 5255], [3886, 984], [571, 5473, 892, 4609], [1437, 212, 1590, 5579, 1895, 660], [5418, 421], [288, 1796, 130], [5280, 655], [6955, 4400, 4576, 2887, 3283, 601, 941], [5281, 2571, 2031], [2329, 387, 1553, 2456], [4213, 1012], [2160, 4843, 4138, 2220], [6179, 1731, 3245], [425, 830, 3216, 3010, 3101, 639], [4366, 3637], [2680, 1954], [408, 1500], [569, 1540, 176], [6180, 2155, 5213], [2488, 4809], [5393, 1963, 2555], [6181, 1167, 2066], [2885, 5288], [2886, 4844], [4367, 2950], [66, 5327, 2498, 3510, 2921], [2330, 379, 1064], [7142, 6411], [6184, 4420, 3997, 4059], [886, 2965, 1263, 1829, 1557, 2127], [4734, 5289, 1255, 3928, 1524], [775, 955, 6042], [119, 6466, 3276, 4008], [2212, 170, 1311, 521], [2567, 5319, 2694, 7330, 3694], [1891, 3377], [6187, 6874], [6188, 3252, 4389], [6189, 572, 2697, 5667, 188], [5291, 267, 1025, 1349, 683], [5292, 1217], [4372, 2995], [3074, 442, 2055], [3462, 7125], [2683, 6921], [2684, 3915, 840], [4373, 6981], [5693, 318], [2332, 908, 4486, 2855], [791, 4870], [5996, 7506, 2834], [1430, 5992], [5001, 3977, 4088, 2191], [5466, 6326, 4859], [6195, 4377, 1627, 5886], [4375, 5791], [458, 1160, 912], [2333, 6333], [805, 1214], [5577, 2804], [4378, 2997], [6966, 549, 885, 158, 48, 4813, 4338, 6590, 400, 189], [7172, 85, 334, 5796, 7233, 7487], [3893, 472], [4380, 6060, 4274], [6197, 6512], [6199, 6314, 252], [3358, 5311], [3042, 6100, 1257, 2861], [4383, 6245], [2321, 940], [414, 471, 6070], [3044, 902], [2264, 2105, 5681], [887, 3293, 4129], [6202, 4613, 7476], [5859, 6227], [979, 1745, 5610, 2633], [6971, 5092, 659], [150, 330], [4386, 643, 214, 80, 4104], [3898, 3329], [6205, 488], [6973, 5341, 3629, 29], [4165, 2183], [2687, 5543], [519, 1438], [6974, 7569], [1428, 6707, 6043], [5313, 5709], [3900, 1892, 2540], [1109, 7080, 2374, 842, 2648, 3840], [5315, 2700, 753, 1665], [430, 1906, 353, 7015], [1990, 1371, 3813, 3229, 6558, 5866, 599], [261, 2024, 313, 824, 1870], [6207, 3512, 4561, 5094], [156, 1409], [846, 3361], [4392, 346], [3191, 1597, 1170], [507, 1358, 2173], [4394, 161, 4061], [2339, 1130], [2891, 285, 427, 5624, 7333, 7334, 2842, 2079], [4300, 689], [4397, 4680, 5793], [4398, 621], [1232, 4529], [6613, 79, 5621, 734], [3472, 5540], [6986, 580], [702, 5684], [1069, 7268], [107, 5883], [6988, 679, 4581, 629], [7492, 2547], [2217, 3716], [5325, 290, 179, 741], [5326, 4494], [2894, 628], [6213, 5391], [90, 7231, 765, 3064, 1792], [2895, 2359], [688, 5367, 2149], [1646, 5477, 3556, 4704, 5668, 4826, 5014], [2497, 1383, 253], [2896, 1572], [860, 5461], [6990, 2998, 5882, 6033, 6034, 174], [2669, 2828], [339, 5723, 1908, 6380, 812, 3583, 4822, 1784], [2340, 3249, 4546, 7436, 2610], [5198, 761, 5342, 225], [6215, 871, 849], [4183, 3289], [6216, 7197], [4403, 4634], [4404, 998], [3909, 969, 3309, 1650, 4017], [1104, 1707, 6557], [9, 6374, 18, 6746, 1306, 2087], [5329, 1455], [94, 4519, 163, 4130, 3398, 1095], [5330, 3231, 4913, 7571, 5353], [3474, 236, 229, 2599, 283, 1777, 3136, 1303], [1305, 1319, 2805, 7296, 1423], [1070, 2939], [624, 190, 1750, 3337], [7361, 2551], [4959, 3820], [6219, 2985, 651], [1803, 2454, 2843], [5334, 3492, 4060], [5336, 6053], [1992, 4406, 3969, 4296, 3354], [7518, 7183], [1180, 6300, 6862], [2448, 807, 5120], [3916, 3047, 3670, 2037], [540, 5712, 729], [6222, 6439], [1538, 3095, 3408], [1140, 4794], [3477, 2987, 4215], [6998, 3917], [7001, 6690], [760, 2690, 2134, 6872, 6873], [391, 325, 494, 1161], [4409, 1888, 389, 7284], [5340, 4528], [2449, 1022, 2798], [4412, 7472], [676, 937], [3919, 2653, 577], [284, 1852, 56, 327, 6623, 6], [6225, 7190], [3479, 1680], [3921, 4430, 6983], [2218, 4935, 2860], [4413, 5363, 2629], [2899, 386, 206], [5345, 1943, 5846, 1238], [7007, 4005, 837], [3480, 5304], [5724, 5963], [641, 2103, 5643], [2857, 269, 1472, 6782], [235, 7165], [3923, 121], [4414, 6338], [2691, 4570, 1824], [1141, 103], [1483, 4677], [6641, 4128], [7012, 30], [5352, 2696, 1635], [1439, 5166], [2221, 3365], [4419, 4911], [1518, 4478, 3679, 4927, 1345, 3770], [3924, 4202], [5332, 3697], [3925, 1433], [3196, 6494], [5087, 6081], [4421, 6440, 6624, 6116], [722, 1204, 1010, 7540, 1879], [5355, 5435, 7158, 7270, 3087, 7485, 5951, 4242, 5060], [2779, 3411], [3927, 1484, 878, 1609, 982, 3794], [1200, 4121], [2902, 6689], [6232, 5096], [717, 2347], [3791, 5113, 4250, 6059, 7568], [5356, 1727, 7356], [6235, 7609], [3198, 814, 1737], [4425, 3484], [2104, 262, 4601, 1832, 2269], [970, 69], [4162, 3970, 1998, 838], [2693, 2510, 2254, 3335, 2057, 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6040], [1947, 1185], [483, 2338], [2165, 424], [3374, 7473], [3379, 3396], [5913, 2431], [4207, 5760], [473, 3419], [2436, 1128], [2826, 5360], [3391, 1970, 1793], [2078, 2853], [2440, 7508], [5974, 2846], [2445, 6106], [6000, 2184, 7543], [5802, 7614], [6003, 6115], [3406, 6015], [3415, 5903], [5788, 1528], [3428, 464]]\n"
     ]
    }
   ],
   "source": [
    "def build_dataset(sentences, words):\n",
    "    \"\"\"\n",
    "    Returns:\n",
    "    data: sentences, but with each word is substituted by its ranking in dictionary\n",
    "    count: list of (word, occurrence)\n",
    "    dictionary: dict, word -> ranking\n",
    "    reverse_dictionary: dict, ranking -> word\n",
    "    \"\"\"\n",
    "    count = list()\n",
    "    #NB We are using keywords, no filters!\n",
    "    count.extend(collections.Counter(words).most_common())\n",
    "    dictionary = dict()\n",
    "    for word, _ in count:\n",
    "        dictionary[word] = len(dictionary)\n",
    "    data = [[dictionary[w] for w in sentence] for sentence in sentences if len(sentences) > 0]\n",
    "    reverse_dictionary = dict(zip(dictionary.values(), dictionary.keys())) \n",
    "    return data, count, dictionary, reverse_dictionary\n",
    "\n",
    "# data, count, dictionary, reverse_dictionary = build_dataset(sentences, words)\n",
    "# try with synonyms:\n",
    "data, count, dictionary, reverse_dictionary = build_dataset(synonyms, words)\n",
    "vocabulary_size = len(count)\n",
    "print('Most common words:', count)  # count is never used\n",
    "print('Sample data', data)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "assert(dictionary.get('the') is None)  # If there is 'the', you havent used a good statistical extractor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Generate a training batch for the skip-gram model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from random import shuffle\n",
    "\n",
    "data_index = 0\n",
    "\n",
    "def generate_batch(data, data_index):\n",
    "    '''\n",
    "    IN\n",
    "    data: XXX\n",
    "    data_index: index of sentence\n",
    "    OUT\n",
    "    batch: nparray (variable length) of words\n",
    "    label: nparray (same length as batch, 1) of context words\n",
    "    data_index: data_index + 1\n",
    "    '''\n",
    "    combinations = np.asarray([w for w in itertools.product(data[data_index][:12], data[data_index][:12]) if w[0] != w[1]], dtype=np.int32)\n",
    "    \n",
    "    batch, l = combinations.T\n",
    "    #labels = np.asarray([l], dtype=np.int32)\n",
    "    labels = np.asarray(l, dtype=np.int32)\n",
    "    del(l)\n",
    "    return batch, labels, (data_index + 1) % len(data)\n",
    "\n",
    "\n",
    "\n",
    "# print('data:', [reverse_dictionary[di] for di in data[:8]])\n",
    "\n",
    "# for num_skips, skip_window in [(2, 1), (4, 2)]:\n",
    "#     data_index = 0\n",
    "#     batch, labels = generate_batch(batch_size=8, num_skips=num_skips, skip_window=skip_window)\n",
    "#     print('\\nwith num_skips = %d and skip_window = %d:' % (num_skips, skip_window))\n",
    "#     print('    batch:', [reverse_dictionary[bi] for bi in batch])\n",
    "#     print('    labels:', [reverse_dictionary[li] for li in labels.reshape(8)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[4307, 6166], [4308, 4711]]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[:2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Ofd1MbBuwiva"
   },
   "source": [
    "#### Train a skip-gram model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def distanza(x, y):\n",
    "    return np.dot(x / np.linalg.norm(x), y / np.linalg.norm(y))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "cellView": "both",
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "collapsed": false,
    "id": "8pQKsV4Vwlzy"
   },
   "outputs": [],
   "source": [
    "embedding_size = 32\n",
    "batch, labels, data_index = generate_batch(data, 0)\n",
    "train_labels = tf.convert_to_tensor(labels, dtype=tf.int32)\n",
    "train_batch = tf.convert_to_tensor(batch, dtype=tf.int32)\n",
    "\n",
    "embeddings = tf.Variable(tf.random_uniform([vocabulary_size, embedding_size], -1.0, 1.0))\n",
    "embedded_input = tf.nn.embedding_lookup(embeddings, train_batch)\n",
    "embedded_labels = tf.nn.embedding_lookup(embeddings, train_labels)\n",
    "\n",
    "#distances_matrix = embedded_labels @ tf.transpose(embeddings)\n",
    "distances_matrix = tf.matmul(embedded_labels, tf.transpose(embeddings))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "graph = tf.Graph()\n",
    "with graph.as_default(), tf.device('/cpu:0'):\n",
    "\n",
    "    # Input data.\n",
    "    train_batch = tf.placeholder(tf.int32, shape=[None])\n",
    "    train_labels = tf.placeholder(tf.int32, shape=[None])\n",
    "\n",
    "    ## Random values to the embedding vectors: M(vocabulary x embedding size)\n",
    "    embeddings = tf.Variable(tf.random_uniform([vocabulary_size, embedding_size], -1.0, 1.0))\n",
    "    \n",
    "    ## Weights and biases\n",
    "    softmax_weights = tf.Variable(\n",
    "        tf.truncated_normal([vocabulary_size, embedding_size],\n",
    "                         stddev=1.0 / math.sqrt(embedding_size)))\n",
    "    softmax_biases = tf.Variable(tf.zeros([vocabulary_size]))\n",
    "\n",
    "    embedded_input = tf.nn.embedding_lookup(embeddings, train_batch)\n",
    "    embedded_labels = tf.nn.embedding_lookup(embeddings, train_labels)\n",
    "\n",
    "    # matrix of embeddings.T * embedded_input, i.e. making the\n",
    "    # scalar product of each embedded word (embedding.T is |V| x d)\n",
    "    # with the input. This is a rough measurement of the distance,\n",
    "    # which must be small for the labels\n",
    "    distances_matrix = tf.matmul(embedded_input, tf.transpose(embeddings))\n",
    "\n",
    "    one_hot_labels = tf.one_hot(train_labels, depth=vocabulary_size)\n",
    "    xe = tf.losses.softmax_cross_entropy(one_hot_labels, distances_matrix)\n",
    "\n",
    "    # The optimizer will optimize the softmax_weights AND the embeddings.\n",
    "    optimizer = tf.train.AdagradOptimizer(1.0).minimize(xe)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "cellView": "both",
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "output_extras": [
      {
       "item_id": 23
      },
      {
       "item_id": 48
      },
      {
       "item_id": 61
      }
     ]
    },
    "colab_type": "code",
    "collapsed": false,
    "executionInfo": {
     "elapsed": 436189,
     "status": "ok",
     "timestamp": 1445965429787,
     "user": {
      "color": "#1FA15D",
      "displayName": "Vincent Vanhoucke",
      "isAnonymous": false,
      "isMe": true,
      "permissionId": "05076109866853157986",
      "photoUrl": "//lh6.googleusercontent.com/-cCJa7dTDcgQ/AAAAAAAAAAI/AAAAAAAACgw/r2EZ_8oYer4/s50-c-k-no/photo.jpg",
      "sessionId": "2f1ffade4c9f20de",
      "userId": "102167687554210253930"
     },
     "user_tz": 420
    },
    "id": "1bQFGceBxrWW",
    "outputId": "5ebd6d9a-33c6-4bcd-bf6d-252b0b6055e4",
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "num_steps = 100001\n",
    "\n",
    "with tf.Session(graph=graph) as session:\n",
    "    tf.global_variables_initializer().run()\n",
    "    print('Initialized')\n",
    "    average_loss = 0.0\n",
    "    data_index = 0\n",
    "    for step in range(num_steps):\n",
    "        if step % int(num_steps / 10) == 0:\n",
    "            print(\"Done step \", step)\n",
    "        try:\n",
    "#            if step % int(num_steps / 10) == 0:\n",
    "#                print(\"Distanza prima: \", distanza(1395, 810))\n",
    "            batch_data, batch_labels, data_index = generate_batch(data, data_index)\n",
    "            feed_dict = {train_batch : batch_data, train_labels : batch_labels}\n",
    "            _, lozz = session.run([optimizer, xe], feed_dict=feed_dict)\n",
    "            average_loss += lozz\n",
    "\n",
    "            if step % int(num_steps / 10) == 0 and step > 0:\n",
    "                average_loss = average_loss / float(num_steps / 10)\n",
    "                print(\"Average \")    \n",
    "                average_loss = 0.0\n",
    "                embeds = embeddings.eval()\n",
    "                \n",
    "                print(\"Distanza: \", distanza(embeds[1395], embeds[810]))            \n",
    "        except:\n",
    "            print(\"Problems with data_index = \", data_index)\n",
    "            data_index += 1\n",
    "            \n",
    "      \n",
    "    final_embeddings = embeddings.eval()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "batch_size = tf.shape(batch_data)[0]\n",
    "\n",
    "init = tf.global_variables_initializer()\n",
    "sess = tf.Session()\n",
    "sess.run(init)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1395\n",
      "810\n"
     ]
    }
   ],
   "source": [
    "print(dictionary['companies'])\n",
    "print(dictionary['company'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: 'subscription',\n",
       " 1: 'email',\n",
       " 2: 'install',\n",
       " 3: 'internet',\n",
       " 4: 'installed',\n",
       " 5: 'account',\n",
       " 6: 'download',\n",
       " 7: 'windows',\n",
       " 8: 'renew',\n",
       " 9: 'devices',\n",
       " 10: 'product',\n",
       " 11: 'laptop',\n",
       " 12: 'license',\n",
       " 13: 'link',\n",
       " 14: 'computer',\n",
       " 15: 'password',\n",
       " 16: 'code',\n",
       " 17: 'freedome',\n",
       " 18: 'device',\n",
       " 19: 'log',\n",
       " 20: 'virus',\n",
       " 21: 'address',\n",
       " 22: 'program',\n",
       " 23: 'mail',\n",
       " 24: 'licence',\n",
       " 25: 'protection',\n",
       " 26: 'virgin',\n",
       " 27: 'expired',\n",
       " 28: 'version',\n",
       " 29: 'fsecure',\n",
       " 30: 'software',\n",
       " 31: 'reinstall',\n",
       " 32: 'page',\n",
       " 33: 'key',\n",
       " 34: 'renewal',\n",
       " 35: 'dont',\n",
       " 36: 'cant',\n",
       " 37: 'purchased',\n",
       " 38: 'website',\n",
       " 39: 'update',\n",
       " 40: 'security',\n",
       " 41: 'click',\n",
       " 42: 'contact',\n",
       " 43: 'purchase',\n",
       " 44: 'chat',\n",
       " 45: 'payment',\n",
       " 46: 'error',\n",
       " 47: 'computers',\n",
       " 48: 'received',\n",
       " 49: 'site',\n",
       " 50: 'uninstall',\n",
       " 51: 'trial',\n",
       " 52: 'agent',\n",
       " 53: 'access',\n",
       " 54: 'customer',\n",
       " 55: 'screen',\n",
       " 56: 'downloaded',\n",
       " 57: 'activate',\n",
       " 58: 'protected',\n",
       " 59: 'issue',\n",
       " 60: 'details',\n",
       " 61: 'option',\n",
       " 62: 'remove',\n",
       " 63: 'add',\n",
       " 64: 'bought',\n",
       " 65: 'licenses',\n",
       " 66: 'login',\n",
       " 67: 'installation',\n",
       " 68: 'renewed',\n",
       " 69: 'valid',\n",
       " 70: 'anti',\n",
       " 71: 'thats',\n",
       " 72: 'using',\n",
       " 73: 'paid',\n",
       " 74: 'app',\n",
       " 75: 'logged',\n",
       " 76: 'via',\n",
       " 77: 'mobile',\n",
       " 78: 'online',\n",
       " 79: 'scan',\n",
       " 80: 'enter',\n",
       " 81: 'media',\n",
       " 82: 'current',\n",
       " 83: 'reset',\n",
       " 84: 'file',\n",
       " 85: 'confirm',\n",
       " 86: 'system',\n",
       " 87: 'secure',\n",
       " 88: 'info',\n",
       " 89: 'mac',\n",
       " 90: 'support',\n",
       " 91: 'web',\n",
       " 92: 'tablet',\n",
       " 93: 'message',\n",
       " 94: 'delete',\n",
       " 95: 'android',\n",
       " 96: 'remote',\n",
       " 97: 'active',\n",
       " 98: 'peter',\n",
       " 99: 'antivirus',\n",
       " 100: 'installing',\n",
       " 101: 'card',\n",
       " 102: 'shows',\n",
       " 103: 'booster',\n",
       " 104: 'machine',\n",
       " 105: 'button',\n",
       " 106: 'reference',\n",
       " 107: 'google',\n",
       " 108: 'instructions',\n",
       " 109: 'browser',\n",
       " 110: 'registered',\n",
       " 111: 'desktop',\n",
       " 112: 'robert',\n",
       " 113: 'licences',\n",
       " 114: 'available',\n",
       " 115: 'ipad',\n",
       " 116: 'vpn',\n",
       " 117: 'however',\n",
       " 118: 'service',\n",
       " 119: 'chrome',\n",
       " 120: 'cancel',\n",
       " 121: 'currently',\n",
       " 122: 'session',\n",
       " 123: 'removed',\n",
       " 124: 'https',\n",
       " 125: 'clicked',\n",
       " 126: 'above',\n",
       " 127: 'register',\n",
       " 128: 'files',\n",
       " 129: 'month',\n",
       " 130: 'upgrade',\n",
       " 131: 'confirmation',\n",
       " 132: 'expire',\n",
       " 133: 'uninstalled',\n",
       " 134: 'emails',\n",
       " 135: 'etc',\n",
       " 136: 'unable',\n",
       " 137: 'connect',\n",
       " 138: 'refund',\n",
       " 139: 'expires',\n",
       " 140: 'several',\n",
       " 141: 'user',\n",
       " 142: 'icon',\n",
       " 143: 'products',\n",
       " 144: 'covered',\n",
       " 145: 'onto',\n",
       " 146: 'iphone',\n",
       " 147: 'cleverbridge',\n",
       " 148: 'wont',\n",
       " 149: 'updates',\n",
       " 150: 'previous',\n",
       " 151: 'colin',\n",
       " 152: 'freedom',\n",
       " 153: 'further',\n",
       " 154: 'banking',\n",
       " 155: 'malware',\n",
       " 156: 'invoice',\n",
       " 157: 'its',\n",
       " 158: 'receive',\n",
       " 159: 'due',\n",
       " 160: 'package',\n",
       " 161: 'create',\n",
       " 162: 'yesterday',\n",
       " 163: 'deleted',\n",
       " 164: 'keeps',\n",
       " 165: 'settings',\n",
       " 166: 'process',\n",
       " 167: 'allow',\n",
       " 168: 'portal',\n",
       " 169: 'mysafe',\n",
       " 170: 'restart',\n",
       " 171: 'brian',\n",
       " 172: 'updated',\n",
       " 173: 'checked',\n",
       " 174: 'martin',\n",
       " 175: 'box',\n",
       " 176: 'load',\n",
       " 177: 'ive',\n",
       " 178: 'richard',\n",
       " 179: 'applet',\n",
       " 180: 'tells',\n",
       " 181: 'tool',\n",
       " 182: 'connected',\n",
       " 183: 'activated',\n",
       " 184: 'appears',\n",
       " 185: 'alan',\n",
       " 186: 'connection',\n",
       " 187: 'blocked',\n",
       " 188: 'works',\n",
       " 189: 'recently',\n",
       " 190: 'existing',\n",
       " 191: 'price',\n",
       " 192: 'english',\n",
       " 193: 'continue',\n",
       " 194: 'ref',\n",
       " 195: 'issues',\n",
       " 196: 'facebook',\n",
       " 197: 'sent',\n",
       " 198: 'installer',\n",
       " 199: 'assistance',\n",
       " 200: 'showing',\n",
       " 201: 'keys',\n",
       " 202: 'period',\n",
       " 203: 'reinstalled',\n",
       " 204: 'bank',\n",
       " 205: 'activation',\n",
       " 206: 'solve',\n",
       " 207: 'problems',\n",
       " 208: 'fix',\n",
       " 209: 'data',\n",
       " 210: 'automatically',\n",
       " 211: 'cover',\n",
       " 212: 'failed',\n",
       " 213: 'application',\n",
       " 214: 'entered',\n",
       " 215: 'pop',\n",
       " 216: 'original',\n",
       " 217: 'jan',\n",
       " 218: 'window',\n",
       " 219: 'william',\n",
       " 220: 'asks',\n",
       " 221: 'cannot',\n",
       " 222: 'subscriptions',\n",
       " 223: 'offer',\n",
       " 224: 'firefox',\n",
       " 225: 'mark',\n",
       " 226: 'reply',\n",
       " 227: 'machines',\n",
       " 228: 'andrew',\n",
       " 229: 'provide',\n",
       " 230: 'options',\n",
       " 231: 'store',\n",
       " 232: 'server',\n",
       " 233: 'codes',\n",
       " 234: 'solution',\n",
       " 235: 'copy',\n",
       " 236: 'provided',\n",
       " 237: 'microsoft',\n",
       " 238: 'messages',\n",
       " 239: 'pcs',\n",
       " 240: 'didnt',\n",
       " 241: 'earlier',\n",
       " 242: 'campaign',\n",
       " 243: 'customers',\n",
       " 244: 'kindly',\n",
       " 245: 'programs',\n",
       " 246: 'resolve',\n",
       " 247: 'ian',\n",
       " 248: 'accounts',\n",
       " 249: 'paypal',\n",
       " 250: 'information',\n",
       " 251: 'credit',\n",
       " 252: 'anne',\n",
       " 253: 'janet',\n",
       " 254: 'resolved',\n",
       " 255: 'client',\n",
       " 256: 'added',\n",
       " 257: 'following',\n",
       " 258: 'correctly',\n",
       " 259: 'contacted',\n",
       " 260: 'programme',\n",
       " 261: 'steps',\n",
       " 262: 'accept',\n",
       " 263: 'request',\n",
       " 264: 'latest',\n",
       " 265: 'james',\n",
       " 266: 'below',\n",
       " 267: 'note',\n",
       " 268: 'search',\n",
       " 269: 'doesnt',\n",
       " 270: 'shall',\n",
       " 271: 'opened',\n",
       " 272: 'type',\n",
       " 273: 'main',\n",
       " 274: 'appear',\n",
       " 275: 'renewing',\n",
       " 276: 'ronald',\n",
       " 277: 'although',\n",
       " 278: 'explorer',\n",
       " 279: 'network',\n",
       " 280: 'switch',\n",
       " 281: 'gives',\n",
       " 282: 'patrick',\n",
       " 283: 'provider',\n",
       " 284: 'downloading',\n",
       " 285: 'complete',\n",
       " 286: 'runs',\n",
       " 287: 'ended',\n",
       " 288: 'upgraded',\n",
       " 289: 'voucher',\n",
       " 290: 'apple',\n",
       " 291: 'dave',\n",
       " 292: 'response',\n",
       " 293: 'forward',\n",
       " 294: 'follow',\n",
       " 295: 'june',\n",
       " 296: 'charles',\n",
       " 297: 'accepted',\n",
       " 298: 'linda',\n",
       " 299: 'created',\n",
       " 300: 'longer',\n",
       " 301: 'checking',\n",
       " 302: 'elaine',\n",
       " 303: 'remotely',\n",
       " 304: 'signed',\n",
       " 305: 'platform',\n",
       " 306: 'helpful',\n",
       " 307: 'followed',\n",
       " 308: 'proceed',\n",
       " 309: 'patricia',\n",
       " 310: 'thankyou',\n",
       " 311: 'don',\n",
       " 312: 'susan',\n",
       " 313: 'stephen',\n",
       " 314: 'properly',\n",
       " 315: 'thomas',\n",
       " 316: 'discount',\n",
       " 317: 'incorrect',\n",
       " 318: 'steve',\n",
       " 319: 'listed',\n",
       " 320: 'sites',\n",
       " 321: 'states',\n",
       " 322: 'cost',\n",
       " 323: 'sending',\n",
       " 324: 'directly',\n",
       " 325: 'manage',\n",
       " 326: 'fixed',\n",
       " 327: 'downloads',\n",
       " 328: 'ticket',\n",
       " 329: 'during',\n",
       " 330: 'previously',\n",
       " 331: 'setup',\n",
       " 332: 'ios',\n",
       " 333: 'items',\n",
       " 334: 'confirmed',\n",
       " 335: 'tab',\n",
       " 336: 'transfer',\n",
       " 337: 'loaded',\n",
       " 338: 'browsing',\n",
       " 339: 'form',\n",
       " 340: 'reboot',\n",
       " 341: 'third',\n",
       " 342: 'assume',\n",
       " 343: 'laptops',\n",
       " 344: 'assist',\n",
       " 345: 'chatting',\n",
       " 346: 'bottom',\n",
       " 347: 'shop',\n",
       " 348: 'hopefully',\n",
       " 349: 'advise',\n",
       " 350: 'invalid',\n",
       " 351: 'anthony',\n",
       " 352: 'march',\n",
       " 353: 'manually',\n",
       " 354: 'regarding',\n",
       " 355: 'users',\n",
       " 356: 'list',\n",
       " 357: 'december',\n",
       " 358: 'confused',\n",
       " 359: 'instead',\n",
       " 360: 'lap',\n",
       " 361: 'norton',\n",
       " 362: 'additional',\n",
       " 363: 'chris',\n",
       " 364: 'mike',\n",
       " 365: 'expiry',\n",
       " 366: 'updating',\n",
       " 367: 'ken',\n",
       " 368: 'http',\n",
       " 369: 'logging',\n",
       " 370: 'features',\n",
       " 371: 'lars',\n",
       " 372: 'registration',\n",
       " 373: 'scanning',\n",
       " 374: 'samsung',\n",
       " 375: 'firewall',\n",
       " 376: 'simply',\n",
       " 377: 'sub',\n",
       " 378: 'regards',\n",
       " 379: 'press',\n",
       " 380: 'macbook',\n",
       " 381: 'within',\n",
       " 382: 'kevin',\n",
       " 383: 'successfully',\n",
       " 384: 'paying',\n",
       " 385: 'status',\n",
       " 386: 'solved',\n",
       " 387: 'sorted',\n",
       " 388: 'nope',\n",
       " 389: 'phones',\n",
       " 390: 'neil',\n",
       " 391: 'manager',\n",
       " 392: 'passwords',\n",
       " 393: 'top',\n",
       " 394: 'sethu',\n",
       " 395: 'choose',\n",
       " 396: 'noticed',\n",
       " 397: 'slow',\n",
       " 398: 'october',\n",
       " 399: 'extra',\n",
       " 400: 'receiving',\n",
       " 401: 'fully',\n",
       " 402: 'per',\n",
       " 403: 'direct',\n",
       " 404: 'setting',\n",
       " 405: 'gmail',\n",
       " 406: 'apps',\n",
       " 407: 'therefore',\n",
       " 408: 'mcafee',\n",
       " 409: 'finnish',\n",
       " 410: 'mails',\n",
       " 411: 'charged',\n",
       " 412: 'cancelled',\n",
       " 413: 'numbers',\n",
       " 414: 'changes',\n",
       " 415: 'twice',\n",
       " 416: 'clicking',\n",
       " 417: 'locked',\n",
       " 418: 'desk',\n",
       " 419: 'restore',\n",
       " 420: 'normal',\n",
       " 421: 'coupon',\n",
       " 422: 'services',\n",
       " 423: 'automatic',\n",
       " 424: 'included',\n",
       " 425: 'extend',\n",
       " 426: 'november',\n",
       " 427: 'completed',\n",
       " 428: 'ill',\n",
       " 429: 'win',\n",
       " 430: 'manual',\n",
       " 431: 'mary',\n",
       " 432: 'disconnected',\n",
       " 433: 'barbara',\n",
       " 434: 'havent',\n",
       " 435: 'trail',\n",
       " 436: 'dan',\n",
       " 437: 'description',\n",
       " 438: 'given',\n",
       " 439: 'multiple',\n",
       " 440: 'contract',\n",
       " 441: 'warning',\n",
       " 442: 'daniel',\n",
       " 443: 'notice',\n",
       " 444: 'payed',\n",
       " 445: 'michael',\n",
       " 446: 'forgot',\n",
       " 447: 'mins',\n",
       " 448: 'folder',\n",
       " 449: 'smartphone',\n",
       " 450: 'august',\n",
       " 451: 'virginmedia',\n",
       " 452: 'buy',\n",
       " 453: 'procedure',\n",
       " 454: 'view',\n",
       " 455: 'method',\n",
       " 456: 'location',\n",
       " 457: 'written',\n",
       " 458: 'happening',\n",
       " 459: 'offered',\n",
       " 460: 'tom',\n",
       " 461: 'requested',\n",
       " 462: 'graham',\n",
       " 463: 'july',\n",
       " 464: 'closed',\n",
       " 465: 'tech',\n",
       " 466: 'licens',\n",
       " 467: 'confusing',\n",
       " 468: 'mentioned',\n",
       " 469: 'kenneth',\n",
       " 470: 'till',\n",
       " 471: 'changed',\n",
       " 472: 'unfortunately',\n",
       " 473: 'double',\n",
       " 474: 'edge',\n",
       " 475: 'include',\n",
       " 476: 'select',\n",
       " 477: 'pressed',\n",
       " 478: 'spam',\n",
       " 479: 'aware',\n",
       " 480: 'order',\n",
       " 481: 'pad',\n",
       " 482: 'pat',\n",
       " 483: 'separate',\n",
       " 484: 'example',\n",
       " 485: 'lock',\n",
       " 486: 'raymond',\n",
       " 487: 'blocking',\n",
       " 488: 'imac',\n",
       " 489: 'url',\n",
       " 490: 'necessary',\n",
       " 491: 'payments',\n",
       " 492: 'recommend',\n",
       " 493: 'kim',\n",
       " 494: 'managed',\n",
       " 495: 'difference',\n",
       " 496: 'text',\n",
       " 497: 'panel',\n",
       " 498: 'patience',\n",
       " 499: 'gary',\n",
       " 500: 'recognise',\n",
       " 501: 'locate',\n",
       " 502: 'uninstalling',\n",
       " 503: 'exe',\n",
       " 504: 'verify',\n",
       " 505: 'auto',\n",
       " 506: 'wendy',\n",
       " 507: 'notification',\n",
       " 508: 'connecting',\n",
       " 509: 'finished',\n",
       " 510: 'crashed',\n",
       " 511: 'pro',\n",
       " 512: 'wifi',\n",
       " 513: 'defender',\n",
       " 514: 'present',\n",
       " 515: 'sms',\n",
       " 516: 'sandra',\n",
       " 517: 'menu',\n",
       " 518: 'release',\n",
       " 519: 'possible',\n",
       " 520: 'allowed',\n",
       " 521: 'restarted',\n",
       " 522: 'username',\n",
       " 523: 'language',\n",
       " 524: 'antti',\n",
       " 525: 'karen',\n",
       " 526: 'reinstalling',\n",
       " 527: 'stated',\n",
       " 528: 'plus',\n",
       " 529: 'changing',\n",
       " 530: 'removal',\n",
       " 531: 'basically',\n",
       " 532: 'rid',\n",
       " 533: 'whether',\n",
       " 534: 'kent',\n",
       " 535: 'spoke',\n",
       " 536: 'scott',\n",
       " 537: 'shown',\n",
       " 538: 'forgotten',\n",
       " 539: 'adress',\n",
       " 540: 'weekend',\n",
       " 541: 'unlock',\n",
       " 542: 'steven',\n",
       " 543: 'suggest',\n",
       " 544: 'require',\n",
       " 545: 'subscribed',\n",
       " 546: 'disabled',\n",
       " 547: 'opening',\n",
       " 548: 'contacting',\n",
       " 549: 'receipt',\n",
       " 550: 'typing',\n",
       " 551: 'buying',\n",
       " 552: 'community',\n",
       " 553: 'technical',\n",
       " 554: 'systems',\n",
       " 555: 'block',\n",
       " 556: 'nicholas',\n",
       " 557: 'mode',\n",
       " 558: 'compatible',\n",
       " 559: 'christopher',\n",
       " 560: 'vista',\n",
       " 561: 'accustomer',\n",
       " 562: 'premium',\n",
       " 563: 'otherwise',\n",
       " 564: 'philip',\n",
       " 565: 'derek',\n",
       " 566: 'report',\n",
       " 567: 'charge',\n",
       " 568: 'released',\n",
       " 569: 'loading',\n",
       " 570: 'showed',\n",
       " 571: 'result',\n",
       " 572: 'worked',\n",
       " 573: 'tools',\n",
       " 574: 'await',\n",
       " 575: 'ends',\n",
       " 576: 'nokia',\n",
       " 577: 'advised',\n",
       " 578: 'joan',\n",
       " 579: 'selected',\n",
       " 580: 'telephone',\n",
       " 581: 'sue',\n",
       " 582: 'disable',\n",
       " 583: 'linked',\n",
       " 584: 'easier',\n",
       " 585: 'prefer',\n",
       " 586: 'send',\n",
       " 587: 'sec',\n",
       " 588: 'input',\n",
       " 589: 'removing',\n",
       " 590: 'catherine',\n",
       " 591: 'total',\n",
       " 592: 'scanner',\n",
       " 593: 'clean',\n",
       " 594: 'ordered',\n",
       " 595: 'control',\n",
       " 596: 'transaction',\n",
       " 597: 'appeared',\n",
       " 598: 'others',\n",
       " 599: 'reminder',\n",
       " 600: 'return',\n",
       " 601: 'administrator',\n",
       " 602: 'april',\n",
       " 603: 'avg',\n",
       " 604: 'causing',\n",
       " 605: 'strange',\n",
       " 606: 'colleague',\n",
       " 607: 'servers',\n",
       " 608: 'appreciate',\n",
       " 609: 'logo',\n",
       " 610: 'spyware',\n",
       " 611: 'amount',\n",
       " 612: 'greg',\n",
       " 613: 'jeff',\n",
       " 614: 'remaining',\n",
       " 615: 'required',\n",
       " 616: 'thru',\n",
       " 617: 'helps',\n",
       " 618: 'local',\n",
       " 619: 'jean',\n",
       " 620: 'screenshot',\n",
       " 621: 'anna',\n",
       " 622: 'related',\n",
       " 623: 'expiring',\n",
       " 624: 'exist',\n",
       " 625: 'feature',\n",
       " 626: 'stuart',\n",
       " 627: 'surely',\n",
       " 628: 'malcolm',\n",
       " 629: 'write',\n",
       " 630: 'speed',\n",
       " 631: 'stopped',\n",
       " 632: 'ups',\n",
       " 633: 'older',\n",
       " 634: 'tina',\n",
       " 635: 'keith',\n",
       " 636: 'advice',\n",
       " 637: 'ones',\n",
       " 638: 'paste',\n",
       " 639: 'extension',\n",
       " 640: 'respond',\n",
       " 641: 'team',\n",
       " 642: 'sign',\n",
       " 643: 'entering',\n",
       " 644: 'pages',\n",
       " 645: 'action',\n",
       " 646: 'seemed',\n",
       " 647: 'links',\n",
       " 648: 'purchasing',\n",
       " 649: 'immediately',\n",
       " 650: 'technician',\n",
       " 651: 'eric',\n",
       " 652: 'marie',\n",
       " 653: 'maria',\n",
       " 654: 'infected',\n",
       " 655: 'mikko',\n",
       " 656: 'lynn',\n",
       " 657: 'alex',\n",
       " 658: 'offers',\n",
       " 659: 'factory',\n",
       " 660: 'fails',\n",
       " 661: 'september',\n",
       " 662: 'isnt',\n",
       " 663: 'instruction',\n",
       " 664: 'serial',\n",
       " 665: 'originally',\n",
       " 666: 'initiate',\n",
       " 667: 'phil',\n",
       " 668: 'caused',\n",
       " 669: 'section',\n",
       " 670: 'colleagues',\n",
       " 671: 'akd',\n",
       " 672: 'sarah',\n",
       " 673: 'promotion',\n",
       " 674: 'based',\n",
       " 675: 'attempt',\n",
       " 676: 'answered',\n",
       " 677: 'parental',\n",
       " 678: 'itself',\n",
       " 679: 'writing',\n",
       " 680: 'ran',\n",
       " 681: 'sold',\n",
       " 682: 'nuzula',\n",
       " 683: 'noted',\n",
       " 684: 'sim',\n",
       " 685: 'looked',\n",
       " 686: 'promo',\n",
       " 687: 'replace',\n",
       " 688: 'joseph',\n",
       " 689: 'webpage',\n",
       " 690: 'gordon',\n",
       " 691: 'repair',\n",
       " 692: 'stops',\n",
       " 693: 'expiration',\n",
       " 694: 'thx',\n",
       " 695: 'finland',\n",
       " 696: 'indeed',\n",
       " 697: 'nor',\n",
       " 698: 'backup',\n",
       " 699: 'prompt',\n",
       " 700: 'goodbye',\n",
       " 701: 'somehow',\n",
       " 702: 'whats',\n",
       " 703: 'item',\n",
       " 704: 'bob',\n",
       " 705: 'according',\n",
       " 706: 'barry',\n",
       " 707: 'profile',\n",
       " 708: 'operating',\n",
       " 709: 'viruses',\n",
       " 710: 'disappeared',\n",
       " 711: 'lets',\n",
       " 712: 'websites',\n",
       " 713: 'whilst',\n",
       " 714: 'boot',\n",
       " 715: 'feedback',\n",
       " 716: 'recommended',\n",
       " 717: 'wondering',\n",
       " 718: 'jim',\n",
       " 719: 'shahriman',\n",
       " 720: 'enable',\n",
       " 721: 'broadband',\n",
       " 722: 'carol',\n",
       " 723: 'clearly',\n",
       " 724: 'boxes',\n",
       " 725: 'takes',\n",
       " 726: 'database',\n",
       " 727: 'success',\n",
       " 728: 'recieved',\n",
       " 729: 'weeks',\n",
       " 730: 'ending',\n",
       " 731: 'sean',\n",
       " 732: 'simple',\n",
       " 733: 'programmes',\n",
       " 734: 'scans',\n",
       " 735: 'normally',\n",
       " 736: 'limited',\n",
       " 737: 'julie',\n",
       " 738: 'tim',\n",
       " 739: 'sons',\n",
       " 740: 'stolen',\n",
       " 741: 'apply',\n",
       " 742: 'conversation',\n",
       " 743: 'hence',\n",
       " 744: 'unknown',\n",
       " 745: 'guniz',\n",
       " 746: 'successful',\n",
       " 747: 'typed',\n",
       " 748: 'instal',\n",
       " 749: 'possibility',\n",
       " 750: 'roger',\n",
       " 751: 'concerned',\n",
       " 752: 'clients',\n",
       " 753: 'perform',\n",
       " 754: 'january',\n",
       " 755: 'missing',\n",
       " 756: 'temporary',\n",
       " 757: 'uses',\n",
       " 758: 'similar',\n",
       " 759: 'suggested',\n",
       " 760: 'laura',\n",
       " 761: 'marko',\n",
       " 762: 'dennis',\n",
       " 763: 'subcription',\n",
       " 764: 'morten',\n",
       " 765: 'supported',\n",
       " 766: 'copied',\n",
       " 767: 'protect',\n",
       " 768: 'annoying',\n",
       " 769: 'disk',\n",
       " 770: 'allows',\n",
       " 771: 'units',\n",
       " 772: 'digit',\n",
       " 773: 'errors',\n",
       " 774: 'activating',\n",
       " 775: 'billing',\n",
       " 776: 'sebastian',\n",
       " 777: 'odd',\n",
       " 778: 'nazula',\n",
       " 779: 'hans',\n",
       " 780: 'maximum',\n",
       " 781: 'michelle',\n",
       " 782: 'lol',\n",
       " 783: 'bryan',\n",
       " 784: 'circle',\n",
       " 785: 'guide',\n",
       " 786: 'university',\n",
       " 787: 'tryed',\n",
       " 788: 'henrik',\n",
       " 789: 'personal',\n",
       " 790: 'bar',\n",
       " 791: 'suppose',\n",
       " 792: 'dutch',\n",
       " 793: 'wifes',\n",
       " 794: 'beginning',\n",
       " 795: 'expert',\n",
       " 796: 'multi',\n",
       " 797: 'pops',\n",
       " 798: 'quickly',\n",
       " 799: 'ensure',\n",
       " 800: 'hacked',\n",
       " 801: 'ideal',\n",
       " 802: 'wrote',\n",
       " 803: 'perhaps',\n",
       " 804: 'record',\n",
       " 805: 'trusted',\n",
       " 806: 'disconnect',\n",
       " 807: 'retrieve',\n",
       " 808: 'refunded',\n",
       " 809: 'pass',\n",
       " 810: 'company',\n",
       " 811: 'everytime',\n",
       " 812: 'format',\n",
       " 813: 'video',\n",
       " 814: 'sharon',\n",
       " 815: 'false',\n",
       " 816: 'function',\n",
       " 817: 'johanna',\n",
       " 818: 'tony',\n",
       " 819: 'switched',\n",
       " 820: 'sylvia',\n",
       " 821: 'outlook',\n",
       " 822: 'scanned',\n",
       " 823: 'loose',\n",
       " 824: 'step',\n",
       " 825: 'wil',\n",
       " 826: 'net',\n",
       " 827: 'reload',\n",
       " 828: 'yep',\n",
       " 829: 'reseller',\n",
       " 830: 'extended',\n",
       " 831: 'christine',\n",
       " 832: 'orders',\n",
       " 833: 'popup',\n",
       " 834: 'trojan',\n",
       " 835: 'partner',\n",
       " 836: 'allready',\n",
       " 837: 'signing',\n",
       " 838: 'specific',\n",
       " 839: 'rob',\n",
       " 840: 'except',\n",
       " 841: 'marcus',\n",
       " 842: 'generate',\n",
       " 843: 'initially',\n",
       " 844: 'stating',\n",
       " 845: 'complaint',\n",
       " 846: 'ignore',\n",
       " 847: 'subscribe',\n",
       " 848: 'temp',\n",
       " 849: 'understanding',\n",
       " 850: 'complicated',\n",
       " 851: 'cheers',\n",
       " 852: 'geoffrey',\n",
       " 853: 'submit',\n",
       " 854: 'opens',\n",
       " 855: 'yrs',\n",
       " 856: 'ihave',\n",
       " 857: 'months',\n",
       " 858: 'non',\n",
       " 859: 'carl',\n",
       " 860: 'talktalk',\n",
       " 861: 'sales',\n",
       " 862: 'evening',\n",
       " 863: 'pack',\n",
       " 864: 'sten',\n",
       " 865: 'addresses',\n",
       " 866: 'located',\n",
       " 867: 'jill',\n",
       " 868: 'ben',\n",
       " 869: 'effect',\n",
       " 870: 'arrived',\n",
       " 871: 'understood',\n",
       " 872: 'starting',\n",
       " 873: 'detected',\n",
       " 874: 'task',\n",
       " 875: 'directed',\n",
       " 876: 'jason',\n",
       " 877: 'galaxy',\n",
       " 878: 'frank',\n",
       " 879: 'helped',\n",
       " 880: 'harmful',\n",
       " 881: 'versions',\n",
       " 882: 'roy',\n",
       " 883: 'ann',\n",
       " 884: 'kaspersky',\n",
       " 885: 'recent',\n",
       " 886: 'matti',\n",
       " 887: 'corporate',\n",
       " 888: 'applications',\n",
       " 889: 'records',\n",
       " 890: 'janne',\n",
       " 891: 'olli',\n",
       " 892: 'results',\n",
       " 893: 'meantime',\n",
       " 894: 'paul',\n",
       " 895: 'letters',\n",
       " 896: 'taken',\n",
       " 897: 'appreciated',\n",
       " 898: 'amanda',\n",
       " 899: 'asap',\n",
       " 900: 'assumed',\n",
       " 901: 'usual',\n",
       " 902: 'yourselves',\n",
       " 903: 'cloud',\n",
       " 904: 'couldnt',\n",
       " 905: 'rebooted',\n",
       " 906: 'subs',\n",
       " 907: 'jens',\n",
       " 908: 'nearly',\n",
       " 909: 'shopping',\n",
       " 910: 'inbox',\n",
       " 911: 'frustrating',\n",
       " 912: 'happens',\n",
       " 913: 'forum',\n",
       " 914: 'confirming',\n",
       " 915: 'lisence',\n",
       " 916: 'associated',\n",
       " 917: 'difficult',\n",
       " 918: 'margaret',\n",
       " 919: 'reported',\n",
       " 920: 'explained',\n",
       " 921: 'yahoo',\n",
       " 922: 'ole',\n",
       " 923: 'informed',\n",
       " 924: 'harry',\n",
       " 925: 'installations',\n",
       " 926: 'deactivate',\n",
       " 927: 'interface',\n",
       " 928: 'replacement',\n",
       " 929: 'younited',\n",
       " 930: 'upload',\n",
       " 931: 'bruce',\n",
       " 932: 'adding',\n",
       " 933: 'unsure',\n",
       " 934: 'escalate',\n",
       " 935: 'tablets',\n",
       " 936: 'cart',\n",
       " 937: 'answers',\n",
       " 938: 'unistall',\n",
       " 939: 'linux',\n",
       " 940: 'suite',\n",
       " 941: 'admin',\n",
       " 942: 'reinstallation',\n",
       " 943: 'helen',\n",
       " 944: 'covers',\n",
       " 945: 'policy',\n",
       " 946: 'nettie',\n",
       " 947: 'carry',\n",
       " 948: 'registering',\n",
       " 949: 'jonas',\n",
       " 950: 'oke',\n",
       " 951: 'print',\n",
       " 952: 'theft',\n",
       " 953: 'annual',\n",
       " 954: 'chatted',\n",
       " 955: 'bill',\n",
       " 956: 'often',\n",
       " 957: 'fee',\n",
       " 958: 'names',\n",
       " 959: 'insert',\n",
       " 960: 'pauline',\n",
       " 961: 'advanced',\n",
       " 962: 'jennifer',\n",
       " 963: 'detect',\n",
       " 964: 'refresh',\n",
       " 965: 'hidden',\n",
       " 966: 'needed',\n",
       " 967: 'unprotected',\n",
       " 968: 'michele',\n",
       " 969: 'prevent',\n",
       " 970: 'validity',\n",
       " 971: 'monthly',\n",
       " 972: 'representative',\n",
       " 973: 'leonardo',\n",
       " 974: 'delay',\n",
       " 975: 'blocks',\n",
       " 976: 'visa',\n",
       " 977: 'reactivate',\n",
       " 978: 'recovery',\n",
       " 979: 'identify',\n",
       " 980: 'applied',\n",
       " 981: 'finish',\n",
       " 982: 'francis',\n",
       " 983: 'area',\n",
       " 984: 'decide',\n",
       " 985: 'douglas',\n",
       " 986: 'jonathan',\n",
       " 987: 'including',\n",
       " 988: 'content',\n",
       " 989: 'starts',\n",
       " 990: 'round',\n",
       " 991: 'speaking',\n",
       " 992: 'browsers',\n",
       " 993: 'common',\n",
       " 994: 'query',\n",
       " 995: 'toshiba',\n",
       " 996: 'retail',\n",
       " 997: 'narendra',\n",
       " 998: 'actual',\n",
       " 999: 'pin',\n",
       " ...}"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reverse_dictionary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0150398\n",
      "1.0\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "4.5329218"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(distanza(1395, 810))\n",
    "print(distanza(2, 2))\n",
    "np.linalg.norm(final_embeddings[9])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2776]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[16161]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "cellView": "both",
    "colab": {
     "autoexec": {
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      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "jjJXYA_XzV79"
   },
   "outputs": [],
   "source": [
    "num_points = 400\n",
    "\n",
    "tsne = TSNE(perplexity=30, n_components=2, init='pca', n_iter=5000)\n",
    "two_d_embeddings = tsne.fit_transform(final_embeddings[1:num_points+1, :])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "cellView": "both",
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     "autoexec": {
      "startup": false,
      "wait_interval": 0
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     "output_extras": [
      {
       "item_id": 1
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    "colab_type": "code",
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    "executionInfo": {
     "elapsed": 4763,
     "status": "ok",
     "timestamp": 1445965465525,
     "user": {
      "color": "#1FA15D",
      "displayName": "Vincent Vanhoucke",
      "isAnonymous": false,
      "isMe": true,
      "permissionId": "05076109866853157986",
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      "sessionId": "2f1ffade4c9f20de",
      "userId": "102167687554210253930"
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     "user_tz": 420
    },
    "id": "o_e0D_UezcDe",
    "outputId": "df22e4a5-e8ec-4e5e-d384-c6cf37c68c34"
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   "outputs": [],
   "source": [
    "def plot(embeddings, labels):\n",
    "    assert embeddings.shape[0] >= len(labels), 'More labels than embeddings'\n",
    "    pylab.figure(figsize=(15,15))  # in inches\n",
    "    for i, label in enumerate(labels):\n",
    "        x, y = embeddings[i,:]\n",
    "        pylab.scatter(x, y)\n",
    "        pylab.annotate(label, xy=(x, y), xytext=(5, 2), textcoords='offset points',\n",
    "                       ha='right', va='bottom')\n",
    "    pylab.show()\n",
    "\n",
    "words = [reverse_dictionary[i] for i in range(1, num_points+1)]\n",
    "plot(two_d_embeddings, words)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "QB5EFrBnpNnc"
   },
   "source": [
    "---\n",
    "\n",
    "Problem\n",
    "-------\n",
    "\n",
    "An alternative to skip-gram is another Word2Vec model called [CBOW](http://arxiv.org/abs/1301.3781) (Continuous Bag of Words). In the CBOW model, instead of predicting a context word from a word vector, you predict a word from the sum of all the word vectors in its context. Implement and evaluate a CBOW model trained on the text8 dataset.\n",
    "\n",
    "---"
   ]
  }
 ],
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