Efficient Spatial Keyword Search Methods for Reflecting Multiple Keyword Domains

In this paper, we propose multiple keyword domain-based spatial keyword search queries, called the Multiple Keyword Domain based range (MKDR) query and k-Nearest Neighbor (MKDkNN) query, and their query processing algorithms. The proposed queries retrieve objects that satisfy the searching conditions for the given environmental conditions of object as well as their spatial and textual relevance. The proposed queries consist of two sub-queries. The first sub-query, called the primary query, identifies a group of geo-textual objects that satisfy the requirements for spatial and textual relevance of the query. The second sub-query, called the refining range query, identifies the geotextual objects that satisfy the requirement for environmental conditions of objects. Because the existing methods for spatial keyword queries cannot efficiently handle the proposed queries, we first categorize the data according to their domains of keywords and simultaneously search multiple indexes constructed for objects in each domain. Since our methods prune the nodes that cannot satisfy environmental conditions in the earlier stage of searching, they reduce the number of refining range queries for MKDR and MKDkNN. Our experimental performance analyses show that our proposed query processing algorithms significantly reduce the query response times of MKDR and MKDkNN.