Abstract
With the continued proliferation of location-based services, a growing number of web-Accessible data objects are geotagged and have text descriptions. An important query over such web objects is the direction-Aware spatial keyword query that aims to retrieve the top-k objects that best match query parameters in terms of spatial distance and textual similarity in a given query direction. In some cases, it can be difficult for users to specify appropriate query parameters. After getting a query result, users may find some desired objects are unexpectedly missing and may therefore question the entire result. Enabling why-not questions in this setting may aid users to retrieve better results, thus improving the overall utility of the query functionality. This paper studies the direction-Aware why-not spatial keyword top-k query problem. We propose efficient query refinement techniques to revive missing objects by minimally modifying users' directionaware queries. Experimental studies demonstrate the efficiency and effectiveness of the proposed techniques.
Originalsprog | Engelsk |
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Titel | Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017 |
Antal sider | 4 |
Forlag | IEEE |
Publikationsdato | 16 maj 2017 |
Sider | 107-110 |
Artikelnummer | 7929947 |
ISBN (Elektronisk) | 9781509065431 |
DOI | |
Status | Udgivet - 16 maj 2017 |
Begivenhed | 33rd IEEE International Conference on Data Engineering, ICDE 2017 - San Diego, USA Varighed: 19 apr. 2017 → 22 apr. 2017 |
Konference
Konference | 33rd IEEE International Conference on Data Engineering, ICDE 2017 |
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Land/Område | USA |
By | San Diego |
Periode | 19/04/2017 → 22/04/2017 |