基于模糊概念网的多Agent个性化信息检索研究

Personalized Information Retrieval Study on Multi-Agent Using Fuzzy Concept Networks

随着计算机网络的快速增长和Web内容的动态变化,通用网络搜索引擎的不足越来越明显.文章提出了一种基于模糊概念网的多Agent个性化信息检索模型,描述了个性化信息检索的过程和检索机制,讨论了应用不同方法的Agent检索效果.实验结果表明,使用个性化多搜索引擎检索的结果比其他搜索引擎检索的结果具有更好的整体性能比,能改善用户需要的检索结果.

With the rapid growth of computer networks and dynamic Web content,the lack of general web search engines are becoming more and more evident.In this paper,a personalized information retrieval model on multi-agent using fuzzy concept networks is proposed.We illustrate the process and retrieval mechanism of personalized information retrieval model,and discuss the effect and influence of applying different types agent.Experimental results indicate that the personalized information retrieval results on multi-agent are more relevant than other search engines and prove that proposed model presents better overall performance and is natural way to improve retrieval results of users needed.