{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T00:27:55Z","timestamp":1777854475632,"version":"3.51.4"},"reference-count":41,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2018,6,14]],"date-time":"2018-06-14T00:00:00Z","timestamp":1528934400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Information Science"],"published-print":{"date-parts":[[2019,2]]},"abstract":"<jats:p>A vital research concern for a personalised recommender system is to target items in the long tail. Studies have shown that sales of the e-commerce platform possess a long-tail character, and niche items in the long tail are challenging to be involved in the recommendation list. Since niche items are defined by the niche market, which is a small market segment, traditional recommendation algorithms focused more on popular items promotion and they do not apply to the niche market. In this article, we aim to find the best users for each niche item and proposed a topic-based hierarchical Bayesian linear regression model for niche item recommendation. We first identify niche items and build niche item subgroups based on descriptive information of items. Moreover, we learn a hierarchical Bayesian linear regression model for each niche item subgroup. Finally, we predict the relevance between users and niche items to provide recommendations. We perform a series of validation experiments on Yahoo Movies dataset and compare the performance of our approach with a set of representative baseline recommender algorithms. The result demonstrates the superior performance of our recommendation approach for niche items.<\/jats:p>","DOI":"10.1177\/0165551518782831","type":"journal-article","created":{"date-parts":[[2018,6,14]],"date-time":"2018-06-14T04:31:45Z","timestamp":1528950705000},"page":"92-104","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Topic-based hierarchical Bayesian linear regression models for niche items recommendation"],"prefix":"10.1177","volume":"45","author":[{"given":"Yezheng","family":"Liu","sequence":"first","affiliation":[{"name":"School of Management, Hefei University of Technology, China; Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Xiong","sequence":"additional","affiliation":[{"name":"School of Management, Hefei University of Technology, China; Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianshan","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Management, Hefei University of Technology, China; Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanchun","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Management, Hefei University of Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thushari","family":"Silva","sequence":"additional","affiliation":[{"name":"Faculty of Information Technology, University of Moratuwa, Sri Lanka"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haifeng","family":"Ling","sequence":"additional","affiliation":[{"name":"School of Management, Hefei University of Technology, China; Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2018,6,14]]},"reference":[{"key":"bibr1-0165551518782831","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-85820-3"},{"key":"bibr2-0165551518782831","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2566622"},{"key":"bibr3-0165551518782831","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2016.02.005"},{"key":"bibr4-0165551518782831","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2007.4338497"},{"key":"bibr5-0165551518782831","first-page":"285","volume-title":"Proceedings of the 10th international conference on world wide web","author":"Sarwar B"},{"key":"bibr6-0165551518782831","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"bibr7-0165551518782831","doi-asserted-by":"crossref","unstructured":"Hu L, Cao L, Wang S, et al. 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