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SVD Recommendations using Tensorflow
import numpy as np
import tensorflow as tf
# Set random seed for reproducibility
np.random.seed(1000)
nb_users = 5000
nb_products = 2000
nb_factors = 500
max_rating = 5
nb_rated_products = 500
top_k_products = 10
# Create a random User-Item matrix
uim = np.zeros((nb_users, nb_products), dtype=np.float32)
for i in range(nb_users):
nbp = np.random.randint(0, nb_products, size=nb_rated_products)
for j in nbp:
uim[i, j] = np.random.randint(1, max_rating+1)
# Create a Tensorflow graph
graph = tf.Graph()
with graph.as_default():
# User-item matrix
user_item_matrix = tf.placeholder(tf.float32, shape=(nb_users, nb_products))
# SVD
St, Ut, Vt = tf.svd(user_item_matrix)
# Compute reduced matrices
Sk = tf.diag(St)[0:nb_factors, 0:nb_factors]
Uk = Ut[:, 0:nb_factors]
Vk = Vt[0:nb_factors, :]
# Compute Su and Si
Su = tf.matmul(Uk, tf.sqrt(Sk))
Si = tf.matmul(tf.sqrt(Sk), Vk)
# Compute user ratings
ratings_t = tf.matmul(Su, Si)
# Pick top k suggestions
best_ratings_t, best_items_t = tf.nn.top_k(ratings_t, top_k_products)
# Create Tensorflow session
session = tf.InteractiveSession(graph=graph)
# Compute the top k suggestions for all users
feed_dict = {
user_item_matrix: uim
}
best_items = session.run([best_items_t], feed_dict=feed_dict)
# Suggestions for user 1000, 1010
for i in range(1000, 1010):
print('User {}: {}'.format(i, best_items[0][i]))
for i in range(1000, 1010):
print('User {}: {}'.format(i, best_items[0][i]))
User 1000: [ 412 867 1040 509 1311 1562 758 1796 636 556]
User 1001: [ 548 88 1299 175 81 1837 282 1555 1796 1902]
User 1002: [ 433 667 460 821 1762 775 1673 278 284 1540]
User 1003: [1823 602 1874 43 1979 1612 1755 857 891 1701]
User 1004: [1700 1312 892 621 194 1919 196 1746 1697 1192]
User 1005: [ 891 221 1112 1387 768 1697 916 485 1673 1515]
User 1006: [ 463 611 1986 1253 175 1362 1112 1811 1045 768]
User 1007: [1170 70 1886 757 412 606 892 1772 1540 1415]
User 1008: [ 757 855 509 329 410 1304 1900 1631 476 284]
User 1009: [ 888 1654 6 1453 735 1745 505 422 1878 1965]
@aimsathiya

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@aimsathiya aimsathiya commented Jul 9, 2018

hello Giuseppe Bonaccorso,

I want to know what is dataset? (the structure of data).
I 'm newbie. I want to put the real data in to it.

Thank you.

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