{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T06:13:03Z","timestamp":1781244783522,"version":"3.54.1"},"reference-count":15,"publisher":"World Scientific Pub Co Pte Ltd","issue":"01","funder":[{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan, R.O.C.","doi-asserted-by":"crossref","award":["MOST 107-2221-E-230-010"],"award-info":[{"award-number":["MOST 107-2221-E-230-010"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Vietnam J. Comp. Sci."],"published-print":{"date-parts":[[2020,2]]},"abstract":"<jats:p> Recently, the advances in communication technologies have made music retrieval easier. Without downloading the music, the users can listen to music through online music websites. This incurs a challenging issue of how to provide the users with an effective online listening service. Although a number of past studies paid attention to this issue, the problems of new user, new item and rating sparsity are not easy to solve. To deal with these problems, in this paper, we propose a novel music recommender system that fuses user contents, music contents and preference ratings to enhance the music recommendation. For dealing with problem of new user, the user similarities are calculated by user profiles instead of traditional ratings. By the user similarities, the unknown ratings can be predicted using user-based Collaborative Filtering (CF). For dealing with problems of rating sparsity and new items, the unknown ratings are initialized by acoustic features and music genre ratings. Because the unknown ratings are initially imputed, the rating data will be enriched. Thereupon, the user preference can be predicted effectively by item-based CF.\u00a0The evaluation results show that our proposed music recommender system performs better than the state-of-the-arts methods in terms of Root Mean Squared Error. <\/jats:p>","DOI":"10.1142\/s2196888820500049","type":"journal-article","created":{"date-parts":[[2019,11,19]],"date-time":"2019-11-19T22:18:40Z","timestamp":1574201920000},"page":"77-92","source":"Crossref","is-referenced-by-count":6,"title":["A Personalized Music Recommender System Using User Contents, Music Contents and Preference Ratings"],"prefix":"10.1142","volume":"07","author":[{"given":"Ja-Hwung","family":"Su","sequence":"first","affiliation":[{"name":"Department of Information Management, Cheng Shiu University, Kaohsiung, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chu-Yu","family":"Chin","sequence":"additional","affiliation":[{"name":"Telecommunication Laboratories, Chunghwa Telecom Co., Ltd., Taoyuan, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi-Wen","family":"Liao","sequence":"additional","affiliation":[{"name":"Department of Information Management, Cheng Shiu University, Kaohsiung, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hsiao-Chuan","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Information Management, Cheng Shiu University, Kaohsiung, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vincent S.","family":"Tseng","sequence":"additional","affiliation":[{"name":"Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sun-Yuan","family":"Hsieh","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"219","published-online":{"date-parts":[[2020,2,5]]},"reference":[{"key":"S2196888820500049BIB001","first-page":"43","volume-title":"Proc. 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Special Interest Group on Information Retrieval","author":"Wang J."}],"container-title":["Vietnam Journal of Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S2196888820500049","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,2,26]],"date-time":"2020-02-26T03:34:08Z","timestamp":1582688048000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S2196888820500049"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2]]},"references-count":15,"journal-issue":{"issue":"01","published-print":{"date-parts":[[2020,2]]}},"alternative-id":["10.1142\/S2196888820500049"],"URL":"https:\/\/doi.org\/10.1142\/s2196888820500049","relation":{},"ISSN":["2196-8888","2196-8896"],"issn-type":[{"value":"2196-8888","type":"print"},{"value":"2196-8896","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,2]]}}}