Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/73489
DC FieldValueLanguage
dc.contributor資管系
dc.creator蔡瑞煌zh_TW
dc.creatorYang, Yu-Hsiang;Tsaih, Rua-Huan;Bhikshu, Huimin
dc.date2011
dc.date.accessioned2015-02-12T04:22:54Z-
dc.date.available2015-02-12T04:22:54Z-
dc.date.issued2015-02-12T04:22:54Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/73489-
dc.description.abstractThe purpose of this study was to propose a multi-layer topic map analysis using co-word analysis of informetrics with Growing Hierarchical Self-Organizing Map (GHSOM). The topic map illustrated the delicate intertwining of subject areas and provided a more explicit illustration of the concepts within each subject area. We applied GHSOM, a text-mining Neural Networks tool, to obtain a hierarchical topic map. After taking up one example of altruism in evaluation, we suggest that topic map may disclose some important facts from a whole bunch of data.
dc.format.extent646754 bytes-
dc.format.mimetypeapplication/pdf-
dc.relationInternational Journal of Digital Content Technology and its Applications,5(3),355-363
dc.subjectTopic-map; Co-word; Growing Hierarchical Self-Organizing Map; GHSOM; Altruism
dc.titleThe Research of Multi-Layer Topic Map Analysis using Co-word Analysis with Growing Hierarchical Self-organizing Map
dc.typearticleen
dc.identifier.doi10.4156/jdcta.vol5.issue3.35en_US
dc.doi.urihttp://dx.doi.org/10.4156/jdcta.vol5.issue3.35en_US
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextrestricted-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.openairetypearticle-
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