Hybrid index structures for location-based web search
Proceedings of the 14th ACM international conference on Information and knowledge management
Processing Spatial-Keyword (SK) Queries in Geographic Information Retrieval (GIR) Systems
SSDBM '07 Proceedings of the 19th International Conference on Scientific and Statistical Database Management
Keyword Search on Spatial Databases
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Keyword Search in Spatial Databases: Towards Searching by Document
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Efficient retrieval of the top-k most relevant spatial web objects
Proceedings of the VLDB Endowment
Efficient and scalable method for processing top-k spatial Boolean queries
SSDBM'10 Proceedings of the 22nd international conference on Scientific and statistical database management
DESKS: Direction-Aware Spatial Keyword Search
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
Seal: spatio-textual similarity search
Proceedings of the VLDB Endowment
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With the ever-increasing number of spatio-textual objects, many applications require to find objects close to a given query point in spatial databases. In this paper, we study the problem of keyword-based k-nearest neighbor search in spatial databases, which, given a query point and a set of keywords, finds k-nearest neighbors of the query point that contain all query keywords. To efficiently answer such queries, we propose a new indexing framework by integrating a spatial component and a textual component, which can efficiently prune search space in terms of both spatial information and textual descriptions. We develop effective index structures and pruning techniques to improve query performance. Experimental results show that our approach significantly outperforms state-of-the-art methods.