doiSerbia

Time-aware collective spatial keyword query

Chen Zijun (School of Information Science and Engineering, Yanshan University, Qinhuangdao, China + The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Qinhuangdao, China), zjchen@ysu.edu.cn
Zhao Tingting (School of Information Science and Engineering, Yanshan University, Qinhuangdao, China), tingtingzhao@stumail.ysu.edu.cn
Liu Wenyuan (School of Information Science and Engineering, Yanshan University, Qinhuangdao, China + The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Qinhuangdao, China), 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.

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