XML 数据流上Top-K 关键字查询处理

利用关键字可以在模式未知的情况下对XML数据进行查询.在当前的XML数据流上的关键字查询处理中,打分函数往往不能都满足各种用户不同的需求.提出了一种基于skyline的XML数据流上的Top-K关键字查询.对于这种查询,不需要考虑影响结果与查询相关性的复杂因素,只需利用skyline挑选与查询最相关的结果.提出了两种XML数据流上的有效的基于skyline的Top-K关键查询处理算法,包括对单查询和多查询的处理算法.通过扩展实验对两种算法的有效性和可扩展性进行了验证.经过实验验证,所提出的查询处理算法的效率几乎不受关键字个数、查询结果数量、查询数量等参数的影响,运行时间和文档大小大致呈线性关系.

Efficient Top-K Keyword Search on XML Streams

Keywords are suitable for query XML streams without schema information.In current forms of keywords search on XML streams and rank functions do not always represent users’ intensions.This paper addresses this problem in another aspect.In this paper,the skyline Top-K keyword queries,a novel kind of keyword queries on XML streams,are presented.For such queries,skyline is used to choose results on XML streams without considering the complicated factors influencing the relevance to queries.With skyline query processing techniques,two techniques,are presented to process skyline Top-K keyword single queries and multi-queries on XML streams efficiently.Extensive experiments are performed to verify the effectiveness and efficiency of these techniques presented in this paper.According to the experimental results,the algorithms are not sensitive to the parameters such as the number of keywords,the number of results,the number of queries,and the runtime is approximately linear to the size of document.