基于模糊概念网络的多代理个性化搜索引擎研究

A Multi-agent Based Personalized Meta-search Engine Using Automatic Fuzzy Concept Networks

由于近年来网络信息的快速增长,导致传统的搜索引擎在检索过程中会返回大量的不相关内容.针对这一问题,提出一种基于模糊概念网络的多代理个性化搜索引擎,主要利用模糊概念网络去学习用户的兴趣,并写入用户配置文件,然后根据用户配置文件去过滤多代理服务器检索出的信息,最终实现一个高效的个性化搜索引擎.实验表明,通过本文提出的搜索引擎检索出的结果要比传统搜索引擎检索出的结果相关度更高.

In recent years,as the result of the rapid growth of network information,large amount of unrelated contents will be returned in the retrieving process using traditional search engine.Aimed at this problem,a multi-agent personalized search engine based on Fuzzy Concept Networks is proposed in this paper.This engine uses Fuzzy Concept Networks to study customer＇s interest and writes these information into the configuration file.Then according to the configuration file,the information retrieved by multi-agent servers is filtered and an efficient personalized search engine is realized.Experimental statistics indicate that the retrieving results of the personalized search engine raised in this article are more relevant than those of the traditional search engines.