{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T04:17:50Z","timestamp":1780373870613,"version":"3.54.1"},"reference-count":44,"publisher":"Emerald","issue":"4","license":[{"start":{"date-parts":[[2022,4,12]],"date-time":"2022-04-12T00:00:00Z","timestamp":1649721600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["ITSE"],"published-print":{"date-parts":[[2022,10,27]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>The purpose of this study is to analyze from multiple perspectives, so as to form an effective massive open online course (MOOC)personalized recommendation method to help learners efficiently obtain MOOC resources.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>This study introduced ontology construction technology and a new semantic association algorithm to form a new MOOC resource personalized recommendation idea. On the one hand, by constructing a learner model and a MOOC resource ontology model, based on the learner\u2019s characteristics, the learner\u2019s MOOC resource learning preference is predicted, and a recommendation list is formed. On the other hand, the semantic association algorithm is used to calculate the correlation between the MOOC resources to be recommended and the learners\u2019 rated resources and predict the learner\u2019s learning preferences to form a recommendation list. Finally, the two recommendation lists were comprehensively analyzed to form the final MOOC resource personalized recommendation list.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The semantic association algorithm based on hierarchical correlation analysis and attribute correlation analysis introduced in this study can effectively analyze the semantic similarity between MOOC resources. The hybrid recommendation method that introduces ontology construction technology and performs semantic association analysis can effectively realize the personalized recommendation of MOOC resources.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>This study has formed an effective method for personalized recommendation of MOOC resources, solved the problems existing in the personalized recommendation that is, the recommendation relies on the learner\u2019s rating of the resource, the recommendation is specialized, and the knowledge structure of the recommended resource is static, and provides a new idea for connecting MOOC learners and resources.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/itse-10-2021-0190","type":"journal-article","created":{"date-parts":[[2022,10,25]],"date-time":"2022-10-25T01:50:24Z","timestamp":1666662624000},"page":"422-440","source":"Crossref","is-referenced-by-count":16,"title":["Research on personalized recommendation of MOOC resources based on ontology"],"prefix":"10.1108","volume":"19","author":[{"given":"Yuanmin","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dexin","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zehui","family":"Zhan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"140","published-online":{"date-parts":[[2022,4,12]]},"reference":[{"issue":"5","key":"key2022102505492025300_ref001","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1080\/13658810500032321","article-title":"Ontological considerations in GIScience","volume":"19","year":"2005","journal-title":"International Journal of Geographical Information Science"},{"issue":"4","key":"key2022102505492025300_ref002","doi-asserted-by":"publisher","first-page":"390","DOI":"10.1504\/ijtel.2020.110048","article-title":"Learning actor ontology for a personalised recommendation in massive open online courses","volume":"12","year":"2020","journal-title":"International Journal of Technology Enhanced Learning"},{"key":"key2022102505492025300_ref003","unstructured":"Atiki, F.Z. and Daoudi, N. 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