Adaptive query relaxation and top‐ k result sorting of fuzzy spatiotemporal data based on XML

Abstract

With the increasing popularity of Extensible Markup Language (XML) for data representation, there is a lot of interest in searching XML data. Due to the structural heterogeneity of XML, it is daunting for users to formulate exact queries and search for accurate answers. Especially when performing queries on fuzzy spatiotemporal data, the imprecision and uncertainty of information make the amount of query results is small or even empty. In this case, query relaxation is necessary. Existing efforts are mainly made on expanding simple queries. Once there are multiple conditions in the query, the existing algorithms often have poor performance. To address this problem, we first propose an adaptive query relaxation algorithm based on XML, which can handle complex queries efficiently. The approach does not depend on any specific domain or user, it can adaptively relax the initial query requirements, and classify the results into two sets after query relaxation. Moreover, the algorithm prestores the potential matching objects in the auxiliary structure, which provides support for efficient query. In addition, after query relaxation, we present the result sorting algorithm to address the problem of information overload. Finally, we report experimental results to show that our algorithms are superior to previous approaches.