Reference Hub1
Research on Recommendation Algorithm Based on Ranking Learning

Research on Recommendation Algorithm Based on Ranking Learning

Xiaoli Zhang
Copyright: © 2019 |Volume: 17 |Issue: 1 |Pages: 14
ISSN: 1539-2937|EISSN: 1539-2929|EISBN13: 9781522563907|DOI: 10.4018/JECO.2019010106
Cite Article Cite Article

MLA

Zhang, Xiaoli. "Research on Recommendation Algorithm Based on Ranking Learning." JECO vol.17, no.1 2019: pp.60-73. http://doi.org/10.4018/JECO.2019010106

APA

Zhang, X. (2019). Research on Recommendation Algorithm Based on Ranking Learning. Journal of Electronic Commerce in Organizations (JECO), 17(1), 60-73. http://doi.org/10.4018/JECO.2019010106

Chicago

Zhang, Xiaoli. "Research on Recommendation Algorithm Based on Ranking Learning," Journal of Electronic Commerce in Organizations (JECO) 17, no.1: 60-73. http://doi.org/10.4018/JECO.2019010106

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

After analyzing the logistic regression and support vector machine's limitation, the author has chosen the learning to rank method to solve the problem of news recommendations. The article proposes two news recommendation methods which were based on Bayesian optimization criterion and RankSVM. In addition, the article also proposes two methods to solve the dynamic change of user interest and recommendation novelty and diversity. The experimental results show that the two methods can get ideal results, and the overall performance of the method based on Bayesian optimization criterion is better than that based on RankSVM.

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.