Please use this identifier to cite or link to this item:
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

View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

Last Week
Last month
Checked on Aug 13, 2017

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.