Demography-Based Hybrid Recommender System for Movie Recommendations

Title

Demography-Based Hybrid Recommender System for Movie Recommendations

Creator

Raju B.K.; Ummesalma M.

Description

Recommender systems have been explored with different research techniques including content-based filtering and collaborative filtering. The main issue is with the cold start problem of how recommendations have to be suggested to a new user in the platform. There is a need for a system which has the ability to recommend items similar to the users demographic category by considering the collaborative interactions of similar categories of users. The proposed hybrid model solves the cold start problem using collaborative, demography, and content-based approaches. The base algorithm for the hybrid model SVDpp produced a root mean squared error (RMSE) of 0.92 on the test data. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Lecture Notes in Electrical Engineering, Vol-840, pp. 49-58.

Date

2022-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Cold start; Collaborative filtering; Content filtering; Demography filtering; SVDpp

Coverage

Raju B.K., Computer Science Department, Christ Deemed to be University, Bengaluru, Karnataka, India; Ummesalma M., Computer Science Department, Christ Deemed to be University, Bengaluru, Karnataka, India

Rights

Restricted Access

Relation

ISSN: 18761100; ISBN: 978-981169011-2

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-16-9012-9_5

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128613560&doi=10.1007%2f978-981-16-9012-9_5&partnerID=40&md5=4ffd38778a771f14158bd2c8acacd2fe