Geodesic
Time-aware Collective Spatial Keyword Query
Computer Science and Information Systems, Tome 18 (2021) no. 3.

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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 
@article{CSIS_2021_18_3_a21,
     author = {Zijun Chen and Tingting Zhao and Wenyuan Liu},
     title = {Time-aware {Collective} {Spatial} {Keyword} {Query}},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {18},
     number = {3},
     year = {2021},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2021_18_3_a21/}
}
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PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/CSIS_2021_18_3_a21/
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Zijun Chen; Tingting Zhao; Wenyuan Liu. Time-aware Collective Spatial Keyword Query. Computer Science and Information Systems, Tome 18 (2021) no. 3. http://geodesic.mathdoc.fr/item/CSIS_2021_18_3_a21/