Formal Concept Analysis Support for Web Document Clustering Based on Social Tagging

被引：0
|
作者：
Ouyang, Chunping [1 ]
Yang, Xiaohua [1 ]
Li, Xiaoyun [1 ]
Liu, Zhiming [1 ]
机构：
[1] Univ S China, Sch Comp Sci & Technol, Hengyang 421001, Peoples R China
来源：
2012 2ND INTERNATIONAL CONFERENCE ON UNCERTAINTY REASONING AND KNOWLEDGE ENGINEERING (URKE) | 2012年
关键词：
formal concept analysis; social tagging; document clustering;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Web document clustering is one of the most important research branches of Clustering Analyzing. The objective of web document clustering is to meet the need of retrieving web document efficiently from massive information in Internet. Recently social tagging is the important form of document organization in web 2.0, and the tagging as a document descriptor is used to improve the effectiveness of web searching. But a web document usually belongs to various category of tagging, which may lead to the difficulty of browsing web document based on single tagging. This paper explores the use of Formal Concept Analysis (FCA) as mathematical tool to analyze the social tagging of web document, and presents a model for web document clustering based on tagging semantic. Furthermore, taking community web site Douban as an example, the model is applied to allow users to tag and serendipitously browse web document using Formal Concept Analysis.
引用
收藏
页码：304 / 307
页数：4
相关论文
共 50 条
  • [41] TVS Based Technique for Efficient Web Document Clustering in Web Search
    Rajasekaran, R. Thalapathi
    Ramesh, R.
    Menaka, R.
    Vanisri, A.
    [J]. BIOSCIENCE BIOTECHNOLOGY RESEARCH COMMUNICATIONS, 2020, 13 (03): : 68 - 73
  • [42] Web Document Clustering Research Based on Granular Computing
    Zheng Shangzhi
    Zhao Xiaolong
    Zhang Buqun
    Bu Hualong
    [J]. PROCEEDINGS OF THE SECOND INTERNATIONAL SYMPOSIUM ON ELECTRONIC COMMERCE AND SECURITY, VOL II, 2009, : 446 - 450
  • [43] Towards Clustering of Web-based Document Structures
    Dehmer, Matthias
    Emmert-Streib, Frank
    Kilian, Juergen
    Zulauf, Andreas
    [J]. PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 10, 2005, 10 : 289 - 294
  • [44] A fuzzy-based algorithm for Web document clustering
    Friedman, M
    Kandel, A
    Schneider, M
    Last, M
    Shapira, B
    Elovici, Y
    Zaafrany, O
    [J]. NAFIPS 2004: ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY, VOLS 1AND 2: FUZZY SETS IN THE HEART OF THE CANADIAN ROCKIES, 2004, : 524 - 527
  • [45] Partitioning-based clustering for Web document categorization
    Boley, D
    Gini, M
    Gross, R
    Han, EH
    Hastings, K
    Karypis, G
    Kumar, V
    Mobasher, B
    Moore, J
    [J]. DECISION SUPPORT SYSTEMS, 1999, 27 (03) : 329 - 341
  • [46] Phrase Based Web Document Clustering: An Indexing Approach
    Singh, Amit Prakash
    Srivastava, Shalini
    Sahu, Sanjib Kumar
    [J]. COMPUTER COMMUNICATION, NETWORKING AND INTERNET SECURITY, 2017, 5 : 481 - 492
  • [47] Social trend tracking by time series based social tagging clustering
    Chen, Shihn-Yuarn
    Tseng, Tzu-Ting
    Ke, Hao-Ren
    Sun, Chuen-Tsai
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (10) : 12807 - 12817
  • [48] Conceptual Design of Document NoSQL Database with Formal Concept Analysis
    Varga, Viorica
    Janosi-Rancz, Katalin Tuende
    Kalman, Balazs
    [J]. ACTA POLYTECHNICA HUNGARICA, 2016, 13 (02) : 229 - 248
  • [49] A formal concept analysis approach for web usage mining
    Zhou, BY
    Hui, SC
    Chang, KY
    [J]. INTELLIGENT INFORMATION PROCESSING II, 2005, 163 : 437 - 441
  • [50] Categorization of Multiple Documents Using Fuzzy Overlapping Clustering Based on Formal Concept Analysis
    Chen, Yi-Hui
    Lu, Eric Jui-Lin
    Cheng, Ya-Wen
    [J]. INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING, 2020, 30 (05) : 631 - 647
12345