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Title: Reverse keyword search for spatio-textual top-k queries in location-based services
Authors: Lin, X
Xu, JL
Hu, HB 
Issue Date: 2016
Publisher: Institute of Electrical and Electronics Engineers
Source: 2016 32nd IEEE International Conference on Data Engineering (ICDE), May 16-20, 2016, Helsinki, Finland, p. 1488-1489 How to cite?
Abstract: This paper proposes a novel query paradigm, namely reverse keyword search for spatio-textual top-k queries (RSTQ). It returns the keywords under which a target object will be a spatio-textual top-k result. To efficiently process the new query, we devise a novel hybrid index KcR-tree to store and summarize the spatial and textual information of objects. To further improve the performance, we propose three query optimization techniques, i.e., KcR*-tree, lazy upper-bound updating, and keyword set filtering. We also extend RSTQ to allow the input location to be a spatial region instead of a point. Experimental results demonstrate the efficiency of our proposed query techniques in terms of both the computational cost and I/O cost.
ISBN: 978-1-5090-2020-1
Appears in Collections:Conference Paper

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