Multicriteria recommendation based on bacterial foraging optimization

International Journal of Intelligent SystemsVolume 37, Issue 2 p. 1618-1645 RESEARCH ARTICLE Multicriteria recommendation based on bacterial foraging optimization Shuang Geng, Shuang Geng orcid.org/0000-0001-8146-0786 College of Management, Shenzhen University, Shenzhen, ChinaSearch for more papers by this authorXiaofu He, Xiaofu He orcid.org/0000-0003-2862-0925 College of Management, Shenzhen University, Shenzhen, ChinaSearch for more papers by this authorYixin Wang, Yixin Wang orcid.org/0000-0002-2789-7909 College of Management, Shenzhen University, Shenzhen, ChinaSearch for more papers by this authorHong Wang, Corresponding Author Hong Wang ms.hongwang@gmail.com orcid.org/0000-0002-4671-6122 College of Management, Shenzhen University, Shenzhen, China Correspondence Hong Wang, College of Management, Shenzhen University, A518, Mingli Building, Xueyuan road 1066 Shenzhen 518071, China. Email: ms.hongwang@gmail.comSearch for more papers by this authorBen Niu, Ben Niu orcid.org/0000-0001-5822-8743 College of Management, Shenzhen University, Shenzhen, ChinaSearch for more papers by this authorKris M. Law, Kris M. Law orcid.org/0000-0003-3659-0033 School of Engineering, Faculty of Science, Engineering and Built Environment, Deakin University, Geelong, AustraliaSearch for more papers by this author Shuang Geng, Shuang Geng orcid.org/0000-0001-8146-0786 College of Management, Shenzhen University, Shenzhen, ChinaSearch for more papers by this authorXiaofu He, Xiaofu He orcid.org/0000-0003-2862-0925 College of Management, Shenzhen University, Shenzhen, ChinaSearch for more papers by this authorYixin Wang, Yixin Wang orcid.org/0000-0002-2789-7909 College of Management, Shenzhen University, Shenzhen, ChinaSearch for more papers by this authorHong Wang, Corresponding Author Hong Wang ms.hongwang@gmail.com orcid.org/0000-0002-4671-6122 College of Management, Shenzhen University, Shenzhen, China Correspondence Hong Wang, College of Management, Shenzhen University, A518, Mingli Building, Xueyuan road 1066 Shenzhen 518071, China. Email: ms.hongwang@gmail.comSearch for more papers by this authorBen Niu, Ben Niu orcid.org/0000-0001-5822-8743 College of Management, Shenzhen University, Shenzhen, ChinaSearch for more papers by this authorKris M. Law, Kris M. Law orcid.org/0000-0003-3659-0033 School of Engineering, Faculty of Science, Engineering and Built Environment, Deakin University, Geelong, AustraliaSearch for more papers by this author First published: 06 October 2021 https://doi.org/10.1002/int.22688Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract Recommender systems assist users to make decisions among a huge volume of options. Accuracy-oriented recommender systems focus on the prediction power of algorithms and neglect that users may appreciate diverse and novel recommendations in real-world scenarios. Thus, this paper proposed a multicriteria recommendation model that can optimize the recommendation accuracy, diversity, novelty, and individual tendency simultaneously. Additionally, a new multiobjective bacterial foraging optimization method is proposed to improve its searching capability and the performance of recommendation model. The proposed optimization-based multicriteria recommendation algorithm is compared with existing methods on both benchmark functions and real-world data sets. The results demonstrate that the proposed algorithm is superior to other recommendation algorithms in most cases. This study provides insights in recommendation system design and draws scholarly attention to the optimization-based recommendation strategy. Open Research DATA AVAILABILITY STATEMENT All relevant data are within the paper. Volume37, Issue2February 2022Pages 1618-1645 RelatedInformation