Correlation Mining and Discovery for Learning Resources
Sharing information and resources on the Internet has become an important activity for education. The use of ubiquitous devices makes possible for learning participants to be engaged in an open and connected social environment, and also allows the learning activities to be performed at any time and...
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creator | Weng, M. M. Kau, B. C. Yen, N. Y. |
description | Sharing information and resources on the Internet has become an important activity for education. The use of ubiquitous devices makes possible for learning participants to be engaged in an open and connected social environment, and also allows the learning activities to be performed at any time and any places. In this study, the discovery of correlation among shared resources is concentrated. A hypothetical scenario is considered that the information, such as photos and thoughts, is applicable to be shared with implicit context (i.e. geographical information) by learners through a practical implementation, PadSCORM, on a mobile device. Two major contributions are achieved. First, the correlations among resources are determined through usage experiences mining and geographical information adjustment. It then assists learners in filtering out redundant information by highlighting the significance of resources. Second, an intelligent searching algorithm is proposed to visualize adaptive routes in order to facilitate search process and to enrich the learning activity. |
doi_str_mv | 10.1109/ICALT.2012.116 |
format | Conference Proceeding |
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First, the correlations among resources are determined through usage experiences mining and geographical information adjustment. It then assists learners in filtering out redundant information by highlighting the significance of resources. Second, an intelligent searching algorithm is proposed to visualize adaptive routes in order to facilitate search process and to enrich the learning activity.</description><subject>Algorithm design and analysis</subject><subject>Context</subject><subject>Correlation</subject><subject>Data mining</subject><subject>Educational institutions</subject><subject>Filtering</subject><subject>Information Filtering</subject><subject>Peravasive Computing</subject><subject>Social Network Analysis</subject><subject>Social network services</subject><subject>Ubiquitous Learning</subject><issn>2161-3761</issn><issn>2161-377X</issn><isbn>9781467316422</isbn><isbn>1467316423</isbn><isbn>9780769547022</isbn><isbn>0769547028</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo9j81LxDAQxeMXuKy9evHSf6BrMklnmqPUT6gI0oO3JU1SiaytJKuw_71xFecy8_gNj_cYOxd8JQTXlw_tVdevgAvIGg9YoanhhLpWxAEO2QIEikoSvRztmVBIUqACOP5nKE5ZkdIbz5M_uBILRu0co9-YbZin8jFMYXotzeTK65Ds_OXjrhznWHbexD169mn-jNanM3Yymk3yxd9esv72pm_vq-7p7idrFTTfVmAIneUkaXTWDp4QDTQDeMUbQ-A1ShxN06h8CutGlVVNg5PaWVcrLZfs4tc2eO_XHzG8m7hbI2AuL-Q33npLUA</recordid><startdate>201207</startdate><enddate>201207</enddate><creator>Weng, M. 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Y.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Weng, M. M.</au><au>Kau, B. C.</au><au>Yen, N. Y.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Correlation Mining and Discovery for Learning Resources</atitle><btitle>2012 IEEE 12th International Conference on Advanced Learning Technologies</btitle><stitle>icalt</stitle><date>2012-07</date><risdate>2012</risdate><spage>181</spage><epage>185</epage><pages>181-185</pages><issn>2161-3761</issn><eissn>2161-377X</eissn><isbn>9781467316422</isbn><isbn>1467316423</isbn><eisbn>9780769547022</eisbn><eisbn>0769547028</eisbn><coden>IEEPAD</coden><abstract>Sharing information and resources on the Internet has become an important activity for education. The use of ubiquitous devices makes possible for learning participants to be engaged in an open and connected social environment, and also allows the learning activities to be performed at any time and any places. In this study, the discovery of correlation among shared resources is concentrated. A hypothetical scenario is considered that the information, such as photos and thoughts, is applicable to be shared with implicit context (i.e. geographical information) by learners through a practical implementation, PadSCORM, on a mobile device. Two major contributions are achieved. First, the correlations among resources are determined through usage experiences mining and geographical information adjustment. It then assists learners in filtering out redundant information by highlighting the significance of resources. Second, an intelligent searching algorithm is proposed to visualize adaptive routes in order to facilitate search process and to enrich the learning activity.</abstract><pub>IEEE</pub><doi>10.1109/ICALT.2012.116</doi><tpages>5</tpages></addata></record> |
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ispartof | 2012 IEEE 12th International Conference on Advanced Learning Technologies, 2012, p.181-185 |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Algorithm design and analysis Context Correlation Data mining Educational institutions Filtering Information Filtering Peravasive Computing Social Network Analysis Social network services Ubiquitous Learning |
title | Correlation Mining and Discovery for Learning Resources |
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