摘要
用户在使用传统的搜索引擎去检索某一主题的相关信息时,需要从几个不同的方面搜索许多站点,组织和整合这些不同站点的信息变得非常重要。为实现跨媒体搜索,文中提出了一种基于Agent的查询分解策略,并将检索结果予以整合。将查询条件分解,能弥补传统图片搜索引擎在多关键词检索方面的不足,提高信息的传播效率。文中给出了例子予以验证。实验证明,查询分解策略能够有效地改善查全率,查准率也能够保持在70%左右。
Using conventional search engines to retrieve relevant information, users must search many sites from several different aspects. Thus it is important to integrate and organize this information from the different sites. It proposes a query relaxation approach based on agent for cross-media meta-search engines. The recall ratio can be improved effectively by gradually relaxing the search terms used for information retrieval and integrating the result sets. It also shows several examples of how the relaxation approach works. The experiments＇ results show a great improvement for increasing recall ratio and also precision ratio maintains about 70%.
出处
《微计算机应用》
2007年第7期722-725,共4页
Microcomputer Applications
