计算机工程 ›› 2010, Vol. 36 ›› Issue (3): 47-50.doi: 10.3969/j.issn.1000-3428.2010.03.016

• 软件技术与数据库 • 上一篇    下一篇

基于关联规则的检索结果聚类优化

王 琼1,张 量2,刘 闯3   

  1. (1. 常熟理工学院信息化办公室,常熟 215500;2. 苏州市职业大学计算机工程系,苏州 215104; 3. 苏州大学计算机科学与技术学院,苏州 215006)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2010-02-05 发布日期:2010-02-05

Search Results Clustering Optimization Based on Association Rules

WANG Qiong1, ZHANG Liang2, LIU Chuang3   

  1. (1. Information Office, Changshu Institute of Technology, Changshu 215500;
    2. Department of Computer Engineering, Suzhou Vocational University, Suzhou 215104;
    3. School of Computer Science &Technology, Soochow University, Suzhou 215006)
  • Received:1900-01-01 Revised:1900-01-01 Online:2010-02-05 Published:2010-02-05

摘要: 根据元搜索引擎以线性列表的方式为用户提供检索结果的现象,提出一种基于关联规则的检索结果聚类优化方法,在经过分词处理后,提取检索结果中标题和摘要的主要关键词集,从而建立关联词矩阵(AWM)及基于TFIDF函数表示的结果特征向量,实现基于AWM的FCM聚类。仿真实验结果表明,该方法能够提高运行效率及聚类的有效性。

关键词: 元搜索引擎, FCM算法, 关联规则, TFIDF函数, 关联词矩阵

Abstract: According to the fact that meta search engines present the search results to the end user with linear lists, a search results clustering optimization method based on association rules is proposed. The objective is to extract the main keyword sets after segmenting the subject and abstract of the search results to build up Associated Word Matrix(AWM) and express the result feature vector based on TFIDF function, so as to realize FCM clustering based on AWM. Simulation experimental results show this method can promote running efficiency and cluster effect.

Key words: meta search engine, FCM algorithm, association rule, TFIDF function, Associated Word Matrix(AWM)

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