摘要
受蚁群觅食行为仿生研究和蚁群系统模型理论所启发,提出了一种基于蚁群计算模型的分布、协作多主体(multi-agent)反应架构的自适应、可伸缩的Web搜索系统模型(MASAIR),其由大量智能主体组成,利用智能主体架构的优异特性,旨在从巨型超文档集合(Web)中自治地搜索特定主题的信息,从而为用户提供迅捷的信息检索服务。详细描述了MASAIR的计算模型及其算法,通过对标准Web文档集的检索仿真实验结果显示:该架构具有对环境改变的鲁棒性和对用户信息需求变更的自适应性。
This paper presents an adaptive and scalable Web search system,based on a multi-agent reactive architecture,which draws inspiration from biological researches on the ant foraging behavior.Its target is to search autonomous information on particular topics,in huge hyper textual collections,such as the Web,exploiting the outstanding properties of the agent architectures,The algorithm has been proven to be robust against environmental alterations and adaptive to user＇s information need changes,discovering valuable evaluation results from standard Web collections.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第15期163-165,169,共4页
Computer Engineering and Applications
基金
浙江省教育厅科研项目(the Research Project of Department of Education of Zhejiang Province of China under Grant No.20040120) 。
关键词
智能主体
信息检索
相似性测量
多主体系统
intelligent agent
information retrieval
similarity measure
multi-agent system
