一种基于查询特性的查询结果缓存与预取方法  

A Query Result Caching and Prefetching Approach Based on Query Characteristics

作　　者：马宏远[1,2] 王斌[1] 

机构地区：[1]中国科学院计算技术研究所,北京100190 [2]中国科学院研究生院,北京100049

出　　处：《中文信息学报》2011年第5期37-43,共7页Journal of Chinese Information Processing

基　　金：国家自然科学基金资助项目(60873166);国家973资助项目(2007CB311103);国家863计划资助项目(2006AA010105);教育部科学技术研究重点资助项目(109028)

摘　　要：针对搜索引擎查询结果缓存与预取问题,该文提出了一种基于查询特性的搜索引擎查询结果缓存与预取方法,该方法包括用来指导预取的查询结果页码预测模型和缓存与预取算法框架,用于提高搜索引擎系统性能。通过对国内某著名中文商业搜索引擎的某段时间的用户查询日志分析得出,用户对不同查询返回的查询结果所浏览的页数具有显著的非均衡性,结合该特性设计查询结果页码预测模型来进行预取和分区缓存。在该搜索引擎两个月的大规模真实用户查询日志上的实验结果表明,与传统的方法相比,该方法可以获得3.5%~8.45%的缓存命中率提升。Query results caching and prefetching is an effective way to enhance the performance of Web search engines.We present an analysis of query logs originated from a famous Chinese Web search engine and describe the characteristics of Web search engine queries.A query results caching and prefetching approach based on query characteristics is proposed in this paper.The approach contains predictive models of query results page number and a caching and prefetching algorithm framework in Web search engines.We then use a real large scale query logs for a period of 2-months to evaluate the approach,in contrast to the traditional methods and theoretical upper bounds.Experimental results show that this approach can achieve 3.5% to 8.45% increase for all requests as compared with state-of-the-art methods.

关 键 词：搜索引擎 性能优化 查询结果 缓存 预取 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]