{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,7,26]],"date-time":"2023-07-26T04:33:42Z","timestamp":1690346022977},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684109","type":"print"},{"value":"9781643684116","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,7,21]],"date-time":"2023-07-21T00:00:00Z","timestamp":1689897600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,7,21]]},"abstract":"<jats:p>To meet the development needs of Chinese learners\u2019 personalized learning in the context of \u201cInternet+\u201d educational applications, this paper proposes to fuse the topic model (LDA)with the convolutional neural network mode (CNN). It helps us obtain the topic information and semantic information of different learning resources. Then we can obtain the corresponding learning resource feature vector. Secondly, we use the TF-IDF and K-nearest neighbor algorithms to vectorize the different persona information and potential interests of the learners. Then we introduce above-mentioned learning resource feature vectors, use the cosine similarity of the multidimensional vectors to calculate the learning interaction degree between the learners and the learning resources. Finally, we use a collaborative filtering recommendation algorithm based on the K-nearest neighbor algorithm to combine the knowledge point feature vectors of learning resources and learners\u2019 results. This study can realize personalized recommendation of learning resources for learners.<\/jats:p>","DOI":"10.3233\/faia230194","type":"book-chapter","created":{"date-parts":[[2023,7,25]],"date-time":"2023-07-25T12:59:23Z","timestamp":1690289963000},"source":"Crossref","is-referenced-by-count":0,"title":["Artificial Intelligence-Based Hybrid Recommendation Algorithm for Learning Resources"],"prefix":"10.3233","author":[{"given":"Weibo","family":"Huang","sequence":"first","affiliation":[{"name":"Modern Education Technology Center, Experimental Teaching Center, Guangdong University of Foreign Studies, Guangzhou, China"}]},{"given":"Mohan","family":"Liu","sequence":"additional","affiliation":[{"name":"School of English Education, Guangdong University of Foreign Studies, Guangzhou, China"}]},{"given":"Hao","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, School of Cyberspace Security, Guangdong University of Foreign Studies, Guangzhou, China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Modern Management Based on Big Data IV"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA230194","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,25]],"date-time":"2023-07-25T12:59:25Z","timestamp":1690289965000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA230194"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,21]]},"ISBN":["9781643684109","9781643684116"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia230194","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,21]]}}}