Adaptive query relaxation and result categorization of fuzzy spatiotemporal data based on XML

被引:4
|
作者
Bai, Luyi [1 ]
He, Aijia [1 ]
Liu, Minghao [1 ]
Zhu, Lin [1 ]
Xing, Yizong [1 ]
机构
[1] Northeastern Univ Qinhuangdao, Sch Comp & Commun Engn, Qinhuangdao 066004, Hebei, Peoples R China
基金
中国国家自然科学基金;
关键词
Contextual preference; Data distribution; Fuzzy spatiotemporal data; Proximity; Query relaxation; Result categorization;
D O I
10.1016/j.eswa.2020.114222
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the rapid development of spatiotemporal information and its applications, querying spatiotemporal data has received considerable attention. Meanwhile, the imprecision and uncertainty of information cannot be ignored in many practical applications. Querying fuzzy spatiotemporal data have become one of the most important topics in academia and industry. Although there have been some achievements in querying aspect, the study about fuzzy spatiotemporal query relaxation is still few. In fact, query relaxation is necessary when the amount of query results is small or even empty, especially in the process of querying fuzzy spatiotemporal data. In this paper, we propose an adaptive query relaxation and result categorization approach for fuzzy spatiotemporal data based on XML, which is compatible with spatiotemporal features when spatiotemporal related queries are performed. The approach does not depend on any specific domain or user, it can adaptively relax the initial query requirements, and classify the results by user context preferences and data distribution after query relaxation. In order to locate the spatiotemporal data quickly and show the corresponding fuzziness apparently, we adopted XML to construct the fuzzy spatiotemporal model for query relaxation because XML data can be represented as a tree model which can flexibly arrange the spatiotemporal nodes at the specified position and mark the fuzziness of nodes on the path. In addition, after query relaxation, we present the results categorization algorithm to address the problem of information overload, and then return a navigation tree to the user. Finally, we launch a comprehensive set of experiments to demonstrate the effectiveness and efficiency of our proposed approach. Results of experiments demonstrate that our adaptive query relaxation and result categorization approach based on XML has higher recall and precision in spatiotemporal related query, and can capture the user's needs and preferences effectively as well.
引用
收藏
页数:19
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