Research on Recommendation Algorithm Based on Ranking Learning

Xiaoli Zhang
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Xiaoli Zhang: Hetao College, Bayannur, China

Journal of Electronic Commerce in Organizations (JECO), 2019, vol. 17, issue 1, 60-73

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.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jeco00:v:17:y:2019:i:1:p:60-73

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