A User Independent Recommendation System for Web Series

Document Type

Conference Article

Publication Title

Lecture Notes in Networks and Systems

Abstract

The number of people streaming content over the Internet has boomed in the recent years. However, streaming platforms have to promote the right kind of titles to the right people in order to keep them interested in using their platform and that is why a recommendation engine is important. Different people choose to like Web series in different ways. Some like to watch multiple shows of their favorite actor, while some prefer some genres over others. Therefore, not only do the recommendations have to be accurate in the sense of similarity, but that similarity also has to be localized to within parameters, set by the user. In this paper, we have proposed a recommendation system that can recommend Web series to a user without any extensive data. Our recommender can recommend TV shows, both using all possible and localized parameters, tailoring the recommendations to exactly what the user wants, without imposing the bias of other users on them.

First Page

595

Last Page

603

DOI

10.1007/978-981-19-4052-1_59

Publication Date

1-1-2023

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