English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 97106/127750 (76%)
Visitors : 33269321      Online Users : 345
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    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
    Song, Fang Shiun
    Keywords: 社群網絡探勘
    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    Historical Document Mining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.
    Reference: [1] 錢實甫編,清代職官年表 (共四冊),中華書局出版社,北京,1980年。
    [2] 趙爾巽等纂修,清史稿 (共五冊),博愛出版社,臺北,1983年。
    [3] 李澍田編,清實錄東北史料全輯 (共三冊),吉林文史出版社,長春,1988年。
    [4] 王充撰,論衡校釋,中華書局,北京,1990年。
    [5] 謝清俊等,中央研究院古籍全文資料庫的發展概要,行政院經濟建設委員會委託研究計畫,1997年。
    [6] 謝清俊等,資訊科技對人文、社會的衝擊與影響期末研究報告,行政院經濟建設委員會委託研究計畫,1997年。
    [7] 二月河,康熙大帝,台經院文化,臺北,2001年。
    [8] 羅鳳珠,臺灣地區中國古籍數位化的現況與展望,第三次兩岸古籍整理研究學術討論會,2001年。
    [9] 杜維運,史學方法論,三民書局出版社,臺北,2001年。
    [10] 張尚斌,詞夾子演算法在專有名詞辨識上的應用─以歷史文件為例,國立臺灣大學資訊工程學系碩士論文,2005年。
    [11] 古鴻廷,清代官制研究,五南圖書出版社,臺北,2005年。
    [12] 朱政吉,由史料中探勘社會網絡:以乾隆時期為例,國立政治大學資訊科學系碩士論文,2008年。
    [13] 闕伯丞,由史料中探勘職官年表:以康熙時期為例,國立政治大學資訊科學系碩士論文,2009年。
    [14] 國史館-數位典藏計畫,http://dftt.drnh.gov.tw/intro-2.htm。
    [15] 漢籍電子文獻,http://hanji.sinica.edu.tw/。
    [16] 清實錄-維基百科,http://zh.wikipedia.org/zh-hk/清實錄。
    [17] R. Agrawal and R. Srikant, 「Fast Algorithms for Mining Association Rules,」 Proceedings of the 20th International Conference on Very Large Data Bases, 1994.
    [18] R. Agrawal and R. Srikant, 「Mining Sequential Patterns,「 Proceedings of International Conference on Data Engineering (ICDE'95), 1995.
    [19] R. L. Breiger, 「The Analysis of Social Networks,「 In Handbook of Data Analysis, London: Sage Publication, 2004.
    [20] A. Clauset, M. E. J. Newman, and C. Moore, 「Finding Community Structure in Very Large Networks, 「 Physical Review E, Vol. 70, No. 6, 2004.
    [21] C. K. Fan and W. H. Tsai, 「Automatic Word Identification in Chinese Sentences by the Relaxation Technique,「 Proceedings of National Computer Symposium, 1987.
    [22] L. Freeman, 「Centrality in Social Networks: Conceptual Clarification,」 Social Networks, Vol. 1, No. 3, 1979.
    [23] J. W. Huang, B. R. Dai, and M. S. Chen, 「Twain: Two-End Association Miner with Precise Frequent Exhibition Periods,」 ACM Transactions on Knowledge Discovery from Data, Vol. 1, No. 2, 2007.
    [24] K. T. Lua and K. W. Gan, 「An Application of Information Theory in Chinese Word Segmentation,」 Journal of Computer Processing of Chinese and Oriental Language, Vol. 8, No. 1, 1994.
    [25] Y. Matsuo, J. Mori, M. Hamasaki, T. Nishimura, H. Takeda, K. Hasida, and M. Ishizuka, 「POLYPHONET: An Advanced Social Network Extraction System from the Web,「 Web Semantics: Science, Services and Agents on the World Wide Web, Vol. 5, 2007.
    [26] M. Newman, 「The Structure and Function of Complex Networks,」 SIAM Review, Vol. 45, No. 2, 2003.
    [27] M. Newman and M. Girvan, 「Finding and Evaluating Community Structure in Network,」 Phys. Rev, 2004.
    [28] J. Y. Nie, M. L. Hannan, and W. Jin, 「Unknown Word Detection and Segmentation of Chinese Using Statistical and Heuristic Knowledge,」 Journal of Communications of the Chinese and Oriental Languages Information Processing Society, Vol. 5, 1995.
    [29] W. D. Nooy, Exploratory Network Analysis with Pajek, New York: Cambridge University Press, 2005.
    [30] R. Srikant and R. Agrawal, 「Mining Sequential Patterns: Generalizations and Performance Improvements,」 In Proc. of 1996 Int. Conf. Extending Database Technology (EDBT'96), 1996.
    [31] S. Wasserman and K. Faust, Social Network Analysis: Methods and Applications, New York: Cambridge University Press, 1994.
    [32] GraphML - Wikipedia, http://en.wikipedia.org/wiki/GraphML
    Description: 碩士
    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

    Files in This Item:

    File SizeFormat

    All items in 政大典藏 are protected by copyright, with all rights reserved.

    社群 sharing

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback