计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (2): 179-181.

• 数据库与信息处理 • 上一篇    下一篇

基于向量相似度修正策略的命名实体关联分析

刘 路,李弼程,张先飞   

  1. 解放军信息工程大学 信息工程学院,郑州 450002
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2008-01-11 发布日期:2008-01-11
  • 通讯作者: 刘 路

Name entity association rules analysis based on modification strategy of vector similarity

LIU Lu,LI Bi-cheng,ZHANG Xian-fei   

  1. Information Engineering Institute,PLA Information Engineering University,Zhengzhou 450002,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2008-01-11 Published:2008-01-11
  • Contact: LIU Lu

摘要: 关联分析是数据挖掘技术中的一种重要方法,代表性算法有FP-growth算法和MAXFP-Miner算法。命名实体包含了文本的主要内容,蕴含了丰富的知识模式。针对命名实体的特点,提出一种基于向量相似度比较的关联规则修正策略,将此修正策略应用于MAXFP-Miner算法中,得到一种改进的MAXFP-Miner算法;利用该算法对命名实体之间的内在联系进行分析,从中发现有意义的知识模式。实验结果与性能比较表明,改进的MAXFP-Miner算法是有效的,优于传统的FP-growth算法和MAXFP-Miner算法。

关键词: 命名实体, 关联分析, MAXFP-Miner, 知识发现

Abstract: Association rules analysis is an important technique of data mining techniques.FP-growth algorithm and MAXFP-Miner algorithm are representative algorithms.Name entities contain main content of the text,include abundant kowledge patterns.Based on the characteristic of the name entities,put forward a modify strategy of vector similarity comparison and applied it to MAXFP-Miner algorithm and gain animproved MAXFP-Miner algorithm.Applied this algorithm to analyze the potential associations the name entities,discover significant knowledge patterns.The result of experiment shows the improved MAXFP-Miner algorithm is effective and better than traditional FP-growth algorithm and MAXFP-Miner algorithm.

Key words: name entity, association rules analysis, MAXFP-Miner, knowledge discovery