{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T20:47:24Z","timestamp":1760042844183,"version":"3.41.2"},"reference-count":15,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2008,4,11]],"date-time":"2008-04-11T00:00:00Z","timestamp":1207872000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2008,4,11]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>This paper aims to explore the feasibility of using web\u2010mining technology on learning object (LO) usage information to discover the LO relation pattern and provide valuable recommendations on related learning resources.<jats:bold><jats:bold>Design\/methodology\/approach<\/jats:bold><\/jats:bold>\u2013 This paper proposes three kinds of learning object relation patterns and gives a specific definition of each pattern based on analysing the learners' usage data stored in the learning object repository. These relation patterns can be used to make effective recommendations to learners.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>LO usage data indicate the potential relation patterns between LOs. By using web\u2010mining technology on the usage data, it is possible to discover valuable relation patterns.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>The authors propose a set of LO relation patterns and indicate how they are closely related to users' learning behaviour.<\/jats:p><\/jats:sec>","DOI":"10.1108\/14684520810879863","type":"journal-article","created":{"date-parts":[[2008,5,4]],"date-time":"2008-05-04T19:53:12Z","timestamp":1209930792000},"page":"254-265","source":"Crossref","is-referenced-by-count":7,"title":["eLORM: learning object relationship mining\u2010based repository"],"prefix":"10.1108","volume":"32","author":[{"given":"Yang","family":"Ouyang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miaoliang","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2022020519493893100_b1","unstructured":"Agrawal, R. and Srikant, R. 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(1995), \u201cAutomatic thesaurus generation for an electronic community system\u201d, Journal of the American Society for Information Science, Vol. 46 No. 3, pp. 175\u201093.","DOI":"10.1002\/(SICI)1097-4571(199504)46:3<175::AID-ASI3>3.0.CO;2-U"},{"key":"key2022020519493893100_b4","doi-asserted-by":"crossref","unstructured":"Farmer, R. and Hughes, B. (2005), \u201cA classification\u2010based framework for learning object assembly\u201d, Proceedings of the 5th International Conference on Advanced Learning Technologies (ICALT 2005), IEEE Computer Society, New York, NY, pp. 4\u20106.","DOI":"10.1109\/ICALT.2005.2"},{"key":"key2022020519493893100_b5","doi-asserted-by":"crossref","unstructured":"Farrell, R., Liburd, S. and Thomas, J. (2004), \u201cDynamic assembly of learning objects\u201d, Proceedings of WWW 2004, ACM Press, New York, NY, pp. 162\u20109.","DOI":"10.1145\/1013367.1013394"},{"key":"key2022020519493893100_b6","unstructured":"Guo, L., Xiang, X. and Shi, Y. (2004), \u201cUse web usage mining to assist online e\u2010learning assessments\u201d, Proceedings of the IEEE International Conference on Advanced Learning Technologies, IEEE Computer Society, New York, NY, 30 August\u20101 September, pp. 912\u20103."},{"key":"key2022020519493893100_b7","doi-asserted-by":"crossref","unstructured":"Ha, S.H., Bae, S.M. and Park, S.C. (2000), \u201cWeb mining for distance education\u201d, Proceedings of the IEEE International Conference on Management of Innovation and Technology (ICMIT 2000), Singapore, 12\u201015 November, Vol. 2, IEEE Computer Society, New York, NY, pp. 715\u20109.","DOI":"10.1109\/ICMIT.2000.916789"},{"key":"key2022020519493893100_b8","unstructured":"IEEE LOM (2001), \u201cIEEE learning technology standardization committee standard for learning object metadata\u201d, available at: http:\/\/ltsc.ieee.org\/wg12\/files\/LOM\/1484\/12\/1\/v1\/FinalDraft.pdf."},{"key":"key2022020519493893100_b9","unstructured":"IMS (2006), \u201cIMS learning resource meta\u2010data specification version 1.3\u201d, available at: www.imsglobal.org\/metadata\/index.html#version1.3."},{"key":"key2022020519493893100_b10","doi-asserted-by":"crossref","unstructured":"Keleberda, I., Repka, V. and Biletskiy, Y. (2006), \u201cSemantic mining based on the learner's preferences\u201d, Proceedings of CCECE '06, Canadian Conference on Electrical and Computer Engineering, Ottawa, Ontario, IEEE Computer Society, New York, NY, pp. 502\u20104.","DOI":"10.1109\/CCECE.2006.277467"},{"key":"key2022020519493893100_b12","unstructured":"S\u00e1nchez\u2010Alonso, S. and Sicilia, M.A. (2004), \u201cRelationships and commitments in learning object metadata\u201d, Proceedings of the 5th International Conference on Information Technology Based Higher Education and Training: ITHET 2004, Istanbul, Turkey."},{"key":"key2022020519493893100_b13","unstructured":"SCORM (2004), \u201cSharable courseware object reference model\u201d, available at: www.adlnet.gov\/news\/articles\/index.aspx?ID=407."},{"key":"key2022020519493893100_b14","doi-asserted-by":"crossref","unstructured":"Srivastava, J., Cooley, R., Deshpand\u00e9, M. and Tan, P.\u2010N. (2000), \u201cWeb usage mining: discovery and applications of usage patterns from web data\u201d, ACM SIGKDD Explorations Newsletter, Vol. 1 No. 2, pp. 12\u201023.","DOI":"10.1145\/846183.846188"},{"key":"key2022020519493893100_b11","unstructured":"Tsai, K.H., Chiu, T.K., Lee, M.C. and Wang, T.I. (2006), \u201cA learning objects recommendation model based on the preference and ontological approaches\u201d, Proceedings of the 6th International Conference on Advanced Learning Technologies, IEEE Computer Society, Washington, DC, pp. 36\u201040."},{"key":"key2022020519493893100_b15","unstructured":"Zaiane, O.R. and Luo, J. (2001), \u201cTowards evaluating learners' behavior in a web\u2010based distance learning environment\u201d, Proceedings of the 2nd IEEE International Conference on Advanced Learning Technologies (ICALT'01), Madison, Wisconsin, 6\u20108 August, IEEE Computer Society, New York, NY, pp. 357\u201060."}],"container-title":["Online Information Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/14684520810879863\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/14684520810879863\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,25]],"date-time":"2025-07-25T00:41:01Z","timestamp":1753404061000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/oir\/article\/32\/2\/254-265\/458161"}},"subtitle":[],"editor":[{"given":"I\u2010Hsien","family":"Ting","sequence":"first","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2008,4,11]]},"references-count":15,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2008,4,11]]}},"alternative-id":["10.1108\/14684520810879863"],"URL":"https:\/\/doi.org\/10.1108\/14684520810879863","relation":{},"ISSN":["1468-4527"],"issn-type":[{"type":"print","value":"1468-4527"}],"subject":[],"published":{"date-parts":[[2008,4,11]]}}}