Welcome to the InfoSci Platform
Reference Hub1
Genetic Algorithm Influenced Top-N Recommender System to Alleviate New User Cold Start Problem

Genetic Algorithm Influenced Top-N Recommender System to Alleviate New User Cold Start Problem

Sharon Moses J., Dhinesh Babu L.D.
Copyright: © 2020 |Volume: 11 |Issue: 2 |Pages: 18
ISSN: 1947-9263|EISSN: 1947-9271|EISBN13: 9781799806707|DOI: 10.4018/IJSIR.2020040104
Cite Article Cite Article

MLA

Sharon Moses J., and Dhinesh Babu L.D. "Genetic Algorithm Influenced Top-N Recommender System to Alleviate New User Cold Start Problem." IJSIR vol.11, no.2 2020: pp.62-79. http://doi.org/10.4018/IJSIR.2020040104

APA

Sharon Moses J. & Dhinesh Babu L.D. (2020). Genetic Algorithm Influenced Top-N Recommender System to Alleviate New User Cold Start Problem. International Journal of Swarm Intelligence Research (IJSIR), 11(2), 62-79. http://doi.org/10.4018/IJSIR.2020040104

Chicago

Sharon Moses J., and Dhinesh Babu L.D. "Genetic Algorithm Influenced Top-N Recommender System to Alleviate New User Cold Start Problem," International Journal of Swarm Intelligence Research (IJSIR) 11, no.2: 62-79. http://doi.org/10.4018/IJSIR.2020040104

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Most recommender systems are based on the familiar collaborative filtering algorithm to suggest items. Quite often, collaborative filtering algorithm fails in generating recommendations due to the lack of adequate user information resulting in new user cold start problem. The cold start problem is one among the prevailing issue in recommendation system where the system fails to render recommendations. To overcome the new user cold start issue, demographical information of the user is utilised as the user information source. Among the demographical information, the impact of the user gender is less explored when compared with other information like age, profession, region, etc. In this work, a genetic algorithm-influenced gender-based top-n recommender algorithm is proposed to address the new user cold start problem. The algorithm utilises the evolution concepts of the genetic algorithm to render top-n recommendations to a new user. The evaluation of the proposed algorithm using real world datasets proved that the algorithm has a better efficiency than the state of art approaches.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.