Basic Keyword Clustering Example in Python

keyword_grouping_in_python.py

import pandas as pd
import numpy as np

from nltk.stem import PorterStemmer, WordNetLemmatizer
from nltk.corpus import stopwords

from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn import cluster

stemmer = PorterStemmer()
sw = stopwords.words('english')

def tokenizer(keyword):
    return [stemmer.stem(w) for w in keyword.split()]

keywords = [
    'campaign building',
    'ppc campaign generator',
    'how to build ppc campaigns',
    'how do you group keywords',
    'how to group keywords',
    'keyword grouper',
    'keyword grouping software',
    'ppc campaign builder',
    'best software to group keywords'
    ]

tfidf = TfidfVectorizer(tokenizer=lemmatize, stop_words=sw)
X = pd.DataFrame(tfidf.fit_transform(keywords).toarray(),
                 index=keywords, columns=tfidf.get_feature_names())
c = cluster.AffinityPropagation()
pred = c.fit_predict(X)

Hi Sir. I just want to ask if this is also available for big sets of keywords. About 12k+ keywords?