Efficient algorithms for answering reverse spatial-keyword nearest neighbor queries

With the proliferation of local services and GPS-enabled mobile phones, reverse spatial-keyword Nearest Neighbor queries are becoming an important type of query. Given a service object (e.g., shop) q as the query, which has a location and a text description, we return customers such that q is one of top-k spatial-keyword relevant service objects for each result customer. Existing algorithms for answering reverse nearest neighbor queries cannot be used for processing reverse spatial-keyword nearest neighbor queries due to the additional text information. To design efficient algorithms, for the first time we theoretically analyze an ideal case, which minimizes the object/index node accesses, for processing reverse spatial-keyword nearest neighbor queries. Under the derived theoretical guidelines, we design novel search algorithms for efficiently answering the queries. Empirical studies show that the proposed algorithms offer scalability and are orders of magnitude faster than existing methods for reverse spatial-keyword nearest neighbor queries.

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