基于P2P的个性化Web信息检索

Peer-to-peer based personalized Web information retrieval

为了克服Web搜索引擎在可扩展性、协作性和个性化等方面存在的不足,提出了一种基于Peer-to-Peer的全分布、协作式、自组织的个性化Web信息检索,定义了以查询主题为中心进行主题聚类、数据组织和查询路由的用户协作共享策略,设计了协作生成用户兴趣列表向量、对相似语义查询进行主题聚类和更新、基于查询集建立倒排索引以及基于查询主题进行语义路由等算法和机制,以提供人性化、协作式、个性化的搜索。模拟实验表明,原型系统可以加快查询速度,减轻网络负荷,提高搜索的准确率。

To overcome the shortcomings of the Web search engines on scalability, collaboration, and personalization, a personalized P2P based Web information retrieval was proposed based on wide distribution, collaboration and self-organization. The strategy of users＇ collaboration and sharing was defined. That is, user＇ s query topics were used to cluster the queries, to store data and to route queries. Towards the goal of providing more humanized and personalized retrieval by utilizing users＇ collaboration, some algorithms and mechanisms were designed in respect to building user＇ s favorite list vector collaboratively, clustering the queries to update the user＇ s interest topic by the semantic similarity, structuring the inverted index based on per unit of keyword group, and forwarding the query among peers according to the similarity of topic. The experimental results show that the prototype system can speed up the searching process, reduce the network load and improve the accuracy of the search.