计算机科学与探索 ›› 2010, Vol. 4 ›› Issue (2): 170-179.DOI: 10.3778/j.issn.1673-9418.2010.02.009

• 学术研究 • 上一篇    下一篇

面向科技主题发展分段的社区核心圈技术

钱铁云1+,李 青1,2,许承瑜1   

  1. 1. 武汉大学 软件工程国家重点实验室,武汉 430072
    2. 香港城市大学 计算机科学系,香港
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2010-02-15 发布日期:2010-02-15
  • 通讯作者: 钱铁云

A Core Group Method for Segmenting the Life Cycle of Scientific Topics

QIAN Tieyun1+, LI Qing1,2, SHEU Phillip1   

  1. 1. State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, China
    2. Department of Computer Science, City University of Hong Kong, Hong Kong, China
  • Received:1900-01-01 Revised:1900-01-01 Online:2010-02-15 Published:2010-02-15
  • Contact: QIAN Tieyun

摘要: 现有的主题发展分析主要集中在总体趋势的识别上,不能回答“该领域目前处于什么发展状态?”等问题。提出了一种新的研究任务,旨在考察科技主题所处的发展状态。为完成此任务,在利用网络社区建模主题的基础上,提出了一种基于社区核心圈的分析技术。按照核心圈生长过程中的分裂期和分裂间期,将主题发展划分为产生、扩张、浸润及收缩四个状态。实验表明,依据社区核心圈可准确判断新兴主题的产生,且其成长模式对整个主题的发展有巨大影响。

关键词: 社会网络分析, 网络社区, 主题周期划分

Abstract: Current research on topic development analysis mainly focuses on finding general trend, thus it can not be used to answer the question like “What state is the topic being at?”. This paper presents a new task which aims to segment the development of a scientific topic into several states. Based on community partitioning in social network, a core group technique is proposed. According to the division phase and interphase in the life cycle of core groups, the development of a topic is separated into four states, i.e. birth state, extending state, saturation state and shrinkage state. Experimental results on a real dataset show that the proposed core group method can accurately judge the generation of a new topic, and the growth pattern of a core group greatly influences the development of its relevant topic.

Key words: social network analysis, network community, topic cycle partitioning

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