{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T08:59:54Z","timestamp":1768813194588,"version":"3.49.0"},"reference-count":29,"publisher":"Wiley","license":[{"start":{"date-parts":[[2020,12,18]],"date-time":"2020-12-18T00:00:00Z","timestamp":1608249600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100009103","name":"Education Department of Shaanxi Province","doi-asserted-by":"publisher","award":["19JK0498"],"award-info":[{"award-number":["19JK0498"]}],"id":[{"id":"10.13039\/501100009103","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009103","name":"Education Department of Shaanxi Province","doi-asserted-by":"publisher","award":["20KY-45"],"award-info":[{"award-number":["20KY-45"]}],"id":[{"id":"10.13039\/501100009103","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Youth Foundation Project of Xi\u2019an Traffic Engineering Institute","award":["19JK0498"],"award-info":[{"award-number":["19JK0498"]}]},{"name":"Youth Foundation Project of Xi\u2019an Traffic Engineering Institute","award":["20KY-45"],"award-info":[{"award-number":["20KY-45"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2020,12,18]]},"abstract":"<jats:p>Collaborative filtering technology is currently the most successful and widely used technology in the recommendation system. It has achieved rapid development in theoretical research and practice. It selects information and similarity relationships based on the user\u2019s history and collects others that are the same as the user\u2019s hobbies. User\u2019s evaluation information is to generate recommendations. The main research is the inadequate combination of context information and the mining of new points of interest in the context-aware recommendation process. On the basis of traditional recommendation technology, in view of the characteristics of the context information in music recommendation, a personalized and personalized music based on popularity prediction is proposed. Recommended algorithm is MRAPP (Media Recommendation Algorithm based on Popularity Prediction). The algorithm first analyzes the user\u2019s contextual information under music recommendation and classifies and models the contextual information. The traditional content-based recommendation technology CB calculates the recommendation results and then, for the problem that content-based recommendation technology cannot recommend new points of interest for users, introduces the concept of popularity. First, we use the memory and forget function to reduce the score and then consider user attributes and product attributes to calculate similarity; secondly, we use logistic regression to train feature weights; finally, appropriate weights are used to combine user-based and item-based collaborative filtering recommendation results. Based on the above improvements, the improved collaborative filtering recommendation algorithm in this paper has greatly improved the prediction accuracy. Through theoretical proof and simulation experiments, the effectiveness of the MRAPP algorithm is demonstrated.<\/jats:p>","DOI":"10.1155\/2020\/6643888","type":"journal-article","created":{"date-parts":[[2020,12,18]],"date-time":"2020-12-18T18:20:43Z","timestamp":1608315643000},"page":"1-11","source":"Crossref","is-referenced-by-count":11,"title":["Personalized Music Recommendation Simulation Based on Improved Collaborative Filtering Algorithm"],"prefix":"10.1155","volume":"2020","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6341-5671","authenticated-orcid":true,"given":"Hui","family":"Ning","sequence":"first","affiliation":[{"name":"The College of Humanities and Economic Management, Xi\u2019an Traffic Engineering Institute, Xi\u2019an 710300, Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Li","sequence":"additional","affiliation":[{"name":"National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.4018\/ijdet.2016070102"},{"issue":"9","key":"2","first-page":"204","article-title":"An improved collaborative filtering recommendation algorithm","volume":"32","author":"L. Yi","year":"2017","journal-title":"Computer and Modernization"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1437\/1\/012024"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1453\/1\/012140"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-11933-5_11"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-018-0816-7"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2016.2631473"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1080\/00949655.2014.907801"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-015-3202-4"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1007\/s00779-019-01343-9"},{"key":"11","first-page":"267","article-title":"A personalized friend recommendation method combining network structure features and interaction information","volume-title":"Advances in Swarm Intelligence","author":"Y. Tan","year":"2018"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.104960"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2016.02.016"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2019.112900"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1111\/exsy.12244"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.08.030"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2018.04.061"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-018-1081-z"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-019-08096-w"},{"issue":"1","key":"20","first-page":"65","article-title":"Personalized recommendation algorithm based on three-dimensional user interest modeling","volume":"41","author":"B. Wang","year":"2015","journal-title":"Computer Engineering"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2912124"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2019.02.002"},{"key":"23","doi-asserted-by":"publisher","DOI":"10.1016\/j.eng.2018.02.005"},{"key":"24","doi-asserted-by":"publisher","DOI":"10.1016\/j.urpr.2015.05.008"},{"key":"25","doi-asserted-by":"publisher","DOI":"10.1177\/1591019917696247"},{"key":"26","doi-asserted-by":"publisher","DOI":"10.1016\/j.leaqua.2017.04.004"},{"key":"27","doi-asserted-by":"publisher","DOI":"10.1109\/tap.2016.2593738"},{"key":"28","doi-asserted-by":"publisher","DOI":"10.1108\/ijcst-03-2017-0036"},{"key":"29","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2016.00474"}],"container-title":["Complexity"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2020\/6643888.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2020\/6643888.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2020\/6643888.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,12,18]],"date-time":"2020-12-18T18:20:54Z","timestamp":1608315654000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/complexity\/2020\/6643888\/"}},"subtitle":[],"editor":[{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2020,12,18]]},"references-count":29,"alternative-id":["6643888","6643888"],"URL":"https:\/\/doi.org\/10.1155\/2020\/6643888","relation":{},"ISSN":["1099-0526","1076-2787"],"issn-type":[{"value":"1099-0526","type":"electronic"},{"value":"1076-2787","type":"print"}],"subject":[],"published":{"date-parts":[[2020,12,18]]}}}