{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T10:36:19Z","timestamp":1766486179123,"version":"3.40.5"},"reference-count":17,"publisher":"Wiley","license":[{"start":{"date-parts":[[2021,10,15]],"date-time":"2021-10-15T00:00:00Z","timestamp":1634256000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Educational Research Fund","award":["SGH20Y1529","YBKT-1801"],"award-info":[{"award-number":["SGH20Y1529","YBKT-1801"]}]},{"name":"Shaanxi Education Bureau","award":["SGH20Y1529","YBKT-1801"],"award-info":[{"award-number":["SGH20Y1529","YBKT-1801"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Mobile Information Systems"],"published-print":{"date-parts":[[2021,10,15]]},"abstract":"<jats:p>Film and television literature recommendation is an AI algorithm that recommends related content according to user preferences and records. The wide application in various APPs and websites provides users with great convenience. This article aims to study the Internet of Things and machine learning technology, combining deep learning, reinforcement learning, and recommendation algorithms, to achieve accurate recommendation of film and television literature. This paper proposes to use the ConvMF-KNN recommendation model to verify and analyze the four models of PMF, ConvM, ConvMF-word2vec, and ConvMF-KNN, respectively, on public datasets. Using the path information between vertices in bipartite graph and considering the degree of vertices, the similarity between items is calculated, and the neighbor item set of items is obtained. The experimental results show that the ConvMF-KNN model combined with the KNN idea effectively improves the recommendation accuracy. Compared with the accuracy of the PMF model on the MovieLens 100 k, MovieLens 1 M, and AIV datasets, the accuracy of the ConvMF model on the above three datasets is 5.26%, 6.31%, and 26.71%, respectively, an increase of 2.26%, 1.22%, and 7.96%. This model is of great significance.<\/jats:p>","DOI":"10.1155\/2021\/4066267","type":"journal-article","created":{"date-parts":[[2021,10,16]],"date-time":"2021-10-16T02:41:28Z","timestamp":1634352088000},"page":"1-10","source":"Crossref","is-referenced-by-count":3,"title":["Research and Application of Film and Television Literature Recommendation Based on Secure Internet of Things and Machine Learning"],"prefix":"10.1155","volume":"2021","author":[{"given":"Jieqiong","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Marxism, Xijing University, Xi\u2019an 710123, Shaanxi, China"},{"name":"Graduate School, The University of Perpetual Help System DALTA, Las Pi\u00f1as Campus, Las Pi\u00f1as City 1740, Philippines"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9811-920X","authenticated-orcid":true,"given":"Zhenhua","family":"Wei","sequence":"additional","affiliation":[{"name":"Graduate School, The University of Perpetual Help System DALTA, Las Pi\u00f1as Campus, Las Pi\u00f1as City 1740, Philippines"},{"name":"Faculty of Education, Xi\u2019an Siyuan University, Xi\u2019an 710038, Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin","family":"Peng","sequence":"additional","affiliation":[{"name":"Graduate School, The University of Perpetual Help System DALTA, Las Pi\u00f1as Campus, Las Pi\u00f1as City 1740, Philippines"},{"name":"Faculty of Education, Xi\u2019an Siyuan University, Xi\u2019an 710038, Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fangchun","family":"Chi","sequence":"additional","affiliation":[{"name":"School of Marxism, Xijing University, Xi\u2019an 710123, Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1007\/s11761-008-0034-3"},{"first-page":"346","article-title":"Using machine learning to secure IoT systems","author":"J. 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Han","year":"2017","journal-title":"International Conference on Future Information & Communication Engineering"}],"container-title":["Mobile Information Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/misy\/2021\/4066267.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/misy\/2021\/4066267.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/misy\/2021\/4066267.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,16]],"date-time":"2021-10-16T02:41:43Z","timestamp":1634352103000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/misy\/2021\/4066267\/"}},"subtitle":[],"editor":[{"given":"Sang-Bing","family":"Tsai","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2021,10,15]]},"references-count":17,"alternative-id":["4066267","4066267"],"URL":"https:\/\/doi.org\/10.1155\/2021\/4066267","relation":{},"ISSN":["1875-905X","1574-017X"],"issn-type":[{"type":"electronic","value":"1875-905X"},{"type":"print","value":"1574-017X"}],"subject":[],"published":{"date-parts":[[2021,10,15]]}}}