政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/74687
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文筆數/總筆數 : 109952/140887 (78%)
造訪人次 : 46289803      線上人數 : 1388
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧：
  • 您可在西文檢索詞彙前後加上"雙引號"，以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋，建議至進階搜尋限定作者欄位，可獲得較完整資料
    •  進階搜尋
    政大機構典藏 > 資訊學院 > 資訊科學系 > 會議論文 >  Item 140.119/74687


    請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/74687


    題名: A better strategy of discovering link-pattern based communities by classical clustering methods
    作者: Lin, C.-Y.;Koh, J.-L.;Chen, Arbee L. P.
    陳良弼
    貢獻者: 資科系
    關鍵詞: Clustering methods;Clustering results;Data clustering;Distance functions;Interaction behavior;Link patterns;Link-pattern based community;Memory utilization;Objective functions;Optimal solutions;Partitioning methods;Social network;Social Networks;Cluster analysis;Data mining;Problem solving;Clustering algorithms
    日期: 2010
    上傳時間: 2015-04-17 17:20:20 (UTC+8)
    摘要: The definition of a community in social networks varies with applications. To generalize different types of communities, the concept of linkpattern based community was proposed in a previous study to group nodes into communities, where the nodes in a community have similar intra-community and inter-community interaction behaviors. In this paper, by defining centroid of a community, a distance function is provided to measure the similarity between the link pattern of a node and the centroid of a community. The problem of discovering link-pattern based communities is transformed into a data clustering problem on nodes for minimizing a given objective function. By extending the partitioning methods of cluster analysis, two algorithms named G-LPC and KM-LPC are proposed to solve the problem. The experiment results show that KM-LPC outperforms the previous work on the efficiency, the memory utilization, and the clustering result. Besides, G-LPC achieves the best result approaching the optimal solution. © 2010 Springer-Verlag Berlin Heidelberg.
    關聯: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    資料類型: conference
    DOI 連結: http://dx.doi.org/10.1007/978-3-642-13657-3_9
    DOI: 10.1007/978-3-642-13657-3_9
    顯示於類別:[資訊科學系] 會議論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    index.html0KbHTML2950檢視/開啟


    在政大典藏中所有的資料項目都受到原著作權保護.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回饋