Answering why-not questions on KNN queries

Zhefan ZHONG, Xin LIN, Liang HE, Jing YANG

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PDF(511 KB)
Front. Comput. Sci. ›› 2019, Vol. 13 ›› Issue (5) : 1062-1071. DOI: 10.1007/s11704-018-7074-4
RESEARCH ARTICLE

Answering why-not questions on KNN queries

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Abstract

Being decades of study, the usability of database systems have received more attention in recent years. Now it is especially able to explain missing objects in a query result, which is called “why-not” questions, and is the focus of concern. This paper studies the problem of answering whynot questions on KNN queries. In our real life, many users would like to use KNN queries to investigate the surrounding circumstances. Nevertheless, they often feel disappointed when finding the result not including their expected objects. In this paper, we use the query refinement approach to resolve the problem. Given the original KNN query and a set of missing objects as input, our algorithm offer a refined KNN query that includes the missing objects to the user. The experimental results demonstrate the efficiency of our proposed optimizations and algorithms.

Keywords

why-not queries / spatio queries / KNN queries / location-based services

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Zhefan ZHONG, Xin LIN, Liang HE, Jing YANG. Answering why-not questions on KNN queries. Front. Comput. Sci., 2019, 13(5): 1062‒1071 https://doi.org/10.1007/s11704-018-7074-4

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