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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/64064


    Title: 應用增長層級式自我組織映射圖於歷年研究主題圖之呈現
    Other Titles: Multi-Layer Visual Presentation of Annual Research Topics Using Growing Hierarchical Self-Organizing Map
    Authors: 姜國輝
    楊喻翔
    Chiang, Johannes K;Yang, Yu-Xiang
    Contributors: 資管系
    Keywords: 增長層級式自我組織映射圖;主題圖;利他;歷年
    Growing Hierarchical Self-Organizing Map (GHSOM);Topic map;Altruism;Annual
    Date: 2012-06
    Issue Date: 2014-02-21 10:57:40 (UTC+8)
    Abstract: 本研究以增長層級式自我組織映射圖（Growing Hierarchical Self-Organizing Map, GHSOM）分析出利他研究文獻中重要的歷年研究主題及概念交涉關係。本研究除了將年度的因素考慮主題分析之外，利用GHSOM除了提供之前自我組織映射圖（Self-Organizing Map, SOM）能重要研究主題上的論文分布情形與主題彼此之間的視覺化，它更改進了SOM的二個缺點，無法自動確定大小的映射圖及表達出資料之間的階層性。本研究利用利他相關文獻作範例，分析結果除了提供這些學科的所關注的主題及學科之間交互關係，有助我們快速掌握研究文獻所呈現的研究概況。
    The purpose of this study was to propose a hierarchical, annual research topic maps using Growing Hierarchical Self-Organizing Map (GHSOM), an improved Self-Organizing Map (SOM) algorithm. Unlike SOM, GHSOM can implement a dynamic architecture automatically and represents the hierarchical relations of results. The topic map illustrated the delicate intertwining of topics of annual research and provided a more explicit illustration of the concepts within each subject area. After taking up one example of altruism, this study suggests that topic map may disclose some important annual research topics from a whole bunch of data.
    Relation: 圖書資訊學研究, 6(2), 1-35
    Source URI: http://www.airitilibrary.com/Publication/alDetailedMesh?DocID=19909128-201206-201207310018-201207310018-1-35
    Data Type: article
    Appears in Collections:[Department of MIS] Periodical Articles

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