Abstract:
Personalization systems compute recommendations based on user information. There are many
kinds of personalization techniques such as
collaborative filtering, content-based filtering, rulebased approach etc. Collaborative filtering (CF) has
become an important data mining technique to make
personalized recommendations for books, web pages
or movies, etc. Collaborative filtering (CF) selects
advertisement for customers based on the opinions of
other customers with similar past preferences.
Memory-based CF predicts users preference based
on their similarity to other user in the database.
This paper presents memory-based CF to predict
for footwear advertisement. Pearson Correlation
Coefficient Similarity algorithm is used to find the
similarity between users.
