{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,12,2]],"date-time":"2023-12-02T00:51:33Z","timestamp":1701478293163},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684444","type":"print"},{"value":"9781643684451","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T00:00:00Z","timestamp":1701302400000},"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":[[2023,11,30]]},"abstract":"<jats:p>In light of the exponential growth of film and television programs, assisting viewers in discovering the desired TV programs from an overwhelming amount of information has become increasingly crucial for television service providers. This study addresses the computational limitations and personal information protection in the dataset by implementing a personalized TV program recommendation based on the item-based collaborative filtering algorithm. In addition to identifying the top-n popular programs, the research also adopts a recommendation strategy for these programs. The accuracy of successfully recommending a single program, which initially stood at 0.34, increases to 0.77 when recommending ten programs. Therefore, effective recommendations bring significant benefits to both television service providers and viewers.<\/jats:p>","DOI":"10.3233\/faia230836","type":"book-chapter","created":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T15:54:31Z","timestamp":1701446071000},"source":"Crossref","is-referenced-by-count":0,"title":["Personalized Television Program Recommendation Based on Item-Based Collaborative Filtering"],"prefix":"10.3233","author":[{"given":"Chenghao","family":"Lei","sequence":"first","affiliation":[{"name":"College of Guangdong-Taiwan Industrial Science and Technology, Dongguan University of Technology, Dongguan, Guangdong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paomin","family":"Tu","sequence":"additional","affiliation":[{"name":"Business School of Yulin Normal University, Yulin City, Guangxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chengte","family":"Lin","sequence":"additional","affiliation":[{"name":"Business School of Yulin Normal University, Yulin City, Guangxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Advances in Artificial Intelligence, Big Data and Algorithms"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA230836","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T15:54:38Z","timestamp":1701446078000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA230836"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,30]]},"ISBN":["9781643684444","9781643684451"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia230836","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,30]]}}}