Synopsis "Recommendation Systems based on Collaborative Filtering"

Collaborative filtering (CF) is a popular recommendation approach that has been extensively researched over the last two decades, resulting in a diverse set of algorithms and a large collection of tools to evaluate their performance. This research proposes a new recommendation approach to deal with the problems of grey sheep and data sparsity, with the aim of improving prediction accuracy by inferring new users from existing users in datasets. This transformation creates users with preferences opposite to those of real users, thereby increasing the number of users and solving the two problems mentioned. The performance of this approach has been evaluated using two datasets, MovieLens and FilmTrust. Overall, this book contributes to the development of better recommender systems capable of overcoming the challenges of data overload and improving user experience.

Customers reviews

Have you read this book? Login to add your review.

More customer reviews

0% (0)
0% (0)
0% (0)
0% (0)
0% (0)

Questions and Answers about the Book

Do you have a question about the book? Login to be able to add your own question.

Opinions about Bookdelivery

More customer reviews

Recommendation Systems based on Collaborative Filtering - Benbrahim, Mohammed ; El Fazziki, Abdellah

Synopsis "Recommendation Systems based on Collaborative Filtering"

Customers reviews

Frequently Asked Questions about the Book

Is the book original?

In what language is the book written?

What is the format of this book?

Questions and Answers about the Book

Opinions about Bookdelivery