Abstract
The proliferation of geo-Textual data gives prominence to spatial keyword search. The basic top-k spatial keyword query, returns k geo-Textual objects that rank the highest according to their textual relevance and spatial proximity to query keywords and a query location. We define, study, and provide means of computing the reverse top-k keyword-based location query. This new type of query takes a set of keywords, a query object q, and a number k as arguments, and it returns a spatial region such that any top-k spatial keyword query with the query keywords and a location in this region would contain object q in its result. This query targets applications in market analysis, geographical planning, and location optimization, and it may support applications related to safe zones and influence zones that are used widely in location-based services. We show that computing an exact query result requires evaluating and merging a set of weighted Voronoi cells, which is expensive. We therefore devise effective algorithms that approximate result regions with quality guarantees. We develop novel pruning techniques on top of an index, and we offer a series of optimization techniques that aim to further accelerate query processing. Empirical studies suggest that the proposed query processing is efficient and scalable.
Original language | English |
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Title of host publication | Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017 |
Number of pages | 12 |
Publisher | IEEE |
Publication date | 16 May 2017 |
Pages | 375-386 |
Article number | 7929992 |
ISBN (Electronic) | 9781509065431 |
DOIs | |
Publication status | Published - 16 May 2017 |
Event | 33rd IEEE International Conference on Data Engineering, ICDE 2017 - San Diego, United States Duration: 19 Apr 2017 → 22 Apr 2017 |
Conference
Conference | 33rd IEEE International Conference on Data Engineering, ICDE 2017 |
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Country/Territory | United States |
City | San Diego |
Period | 19/04/2017 → 22/04/2017 |