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    政大機構典藏 > 理學院 > 資訊科學系 > 學位論文 >  Item 140.119/50993
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/50993


    Title: 由職官年表中利用循序共現樣式探勘人脈網絡
    Social network analysis from official chronology using sequential co-occurrence pattern mining
    Authors: 宋邡熏
    Song, Fang Shiun
    Contributors: 沈錳坤
    Shan ,Man Kwan
    宋邡熏
    Song, Fang Shiun
    Keywords: 社群網絡探勘
    網路中心性
    社群偵測
    史料探勘
    職官年表
    Social Network Mining
    Network Centrality
    Community Detection
    Historical Document Mining
    Official Chronology
    Date: 2009
    Issue Date: 2011-09-29 18:25:10 (UTC+8)
    Abstract: 在政治權力結構中,權臣與派系在其政治人物的社會網絡中扮演重要的角色。本論文研究由職官年表中探勘權臣與派系。我們提出資料探勘演算法由職官年表中探勘循序共現樣式,以探勘出政府官員官職陞貶的共現關係。接著根據所探勘出的循序共現樣式,建立官員之間的社會網絡。透過社會網絡分析中的網絡中心性與社群偵測分別探勘出權臣與派系。本論文以清康熙時期的職官年表實驗驗證。透過視覺化分析顯示本論文所提出的方法有助於歷史學者的研究。
    In a power structure, chief officials and cliques play important roles in the social network and have high influence on politics. This thesis proposes an approach of social network mining from official chronologies to discover the chief officials and the cliques. We propose and develop the algorithm to discover the sequential co-occurrence patterns from official chronologies. Then the social network is constructed based on the discovered sequential co-occurrence patterns. Chief officials are discovered by network centrality analysis while cliques are discovered by community analysis of the constructed social network. The official chronology of Kangxi Emperor is taken as an example for experiments and the visualization analysis demonstrates that the proposed methods are helpful to assist historian for historical research.
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    Description: 碩士
    國立政治大學
    資訊科學學系
    97971009
    98
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0097971009
    Data Type: thesis
    Appears in Collections:[資訊科學系] 學位論文

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