Time-aware Collective Spatial Keyword Query

Zijun Chen1, 2, Tingting Zhao1 and Wenyuan Liu1, 2

  1. School of Information Science and Engineering, Yanshan University
    Qinhuangdao 066004, China
  2. The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province
    Qinhuangdao 066004, China
    zjchen@ysu.edu.cn, tingtingzhao@stumail.ysu.edu.cn, wyliu@ysu.edu.cn


The collective spatial keyword query is a hot research topic in the database community in recent years, which considers both the positional relevance to the query location and textual relevance to the query keywords. However, in real life, the temporal information of object is not always valid. Based on this, we define a new query, namely time-aware collective spatial keyword query (TCoSKQ), which considers the positional relevance, textual relevance, and temporal relevance between objects and query at the same time. Two evaluation functions are defined to meet different needs of users, for each of which we propose an algorithm. Effective pruning strategies are proposed to improve query efficiency based on the two algorithms. Finally, the experimental results show that the proposed algorithms are efficient and scalable.

Key words

Collection of objects, TR-tree, Valid time of the objects, Keyword query

Digital Object Identifier (DOI)


Publication information

Volume 18, Issue 3 (June 2021)
Year of Publication: 2021
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Chen, Z., Zhao, T., Liu, W.: Time-aware Collective Spatial Keyword Query. Computer Science and Information Systems, Vol. 18, No. 3, 1077–1100. (2021), https://doi.org/10.2298/CSIS200131034C