一种基于多Agent的元搜索引擎优化技术研究

针对现有搜索引擎存在的问题,提出基于多Agent的元搜索引擎系统。系统采用元搜索引擎结构,利用多Agent技术,结合数据库的分类和成员引擎的机器学习机制,多Agent通信合作,实现了资源选择的优化。对搜索结果的查询串信息进行相关度分析,将搜索结果位置信息和特征信息的相似度相结合,计算文档的相关评价得分,最后根据评价得分降序对输出文档排序。

Research on Metasearch Engine Optimal Technique Based on Muiti-Agent

For the problems existing in search engine,the metasearch engine system based on the multi-agent is proposed.This system uses metasearch engine structure and multi-agent technology,combines with the classification of database and learning mechanism of members of the engine machine,to realize the resource selection optimization through multi-agent communication cooperation.The correlation analysis of the searching information of results is made,the similarity of the location information and characteristics information calculation are conbined,and the evaluation score of related documents is caculated.At last,it sorts the output document according to the descending order of relevant evaluation score.