| dc.contributor | 資管系 | |
| dc.creator (作者) | 蔡瑞煌 | zh_TW |
| dc.creator (作者) | Yang, Yu-Hsiang;Tsaih, Rua-Huan;Bhikshu, Huimin | |
| dc.date (日期) | 2011 | |
| dc.date.accessioned | 12-Feb-2015 12:22:54 (UTC+8) | - |
| dc.date.available | 12-Feb-2015 12:22:54 (UTC+8) | - |
| dc.date.issued (上傳時間) | 12-Feb-2015 12:22:54 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/73489 | - |
| dc.description.abstract (摘要) | The 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.extent | 646754 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | International Journal of Digital Content Technology and its Applications,5(3),355-363 | |
| dc.subject (關鍵詞) | Topic-map; Co-word; Growing Hierarchical Self-Organizing Map; GHSOM; Altruism | |
| dc.title (題名) | The Research of Multi-Layer Topic Map Analysis using Co-word Analysis with Growing Hierarchical Self-organizing Map | |
| dc.type (資料類型) | article | en |
| dc.identifier.doi (DOI) | 10.4156/jdcta.vol5.issue3.35 | en_US |
| dc.doi.uri (DOI) | http://dx.doi.org/10.4156/jdcta.vol5.issue3.35 | en_US |
