Time-Aware and Direction-Constrained Collective Spatial Keyword Query

Abstract

Collective spatial keyword query (CoSKQ) is an important variant of spatial keyword queries and has become a research hotspot. In real life, user behavior usually has a certain directionality, so they may want to obtain the result object that conforms to a specific direction, which is what the direction-constrained query studies. In addition, query time information also plays an important role in location-based query processing. To this end, this paper takes the lead in studying the Time-aware and Direction-constrained Collective Spatial Keyword Query (TDCoSKQ). To facilitate direction-related operations, space objects are organized using the polar coordinate system. Firstly, an efficient space partition method is designed, and on this basis, a new hybrid index structure KRPQT is designed. Based on KRPQT, several pruning strategies are proposed to prune irrelevant regions and objects from the perspective of keyword, time, and direction, and the basic algorithm KRPQB is proposed. To further improve the efficiency of query processing, the possible areas of the result objects are analyzed and shrunk to greatly reduce the number of candidate objects, and three optimization algorithms KRPSW, KRPSW+LFO, and KRPSW+KRPQB are proposed. Then, we discuss how to extend the proposed methods to deal with TDCoSKQ queries with other distance functions and TDCoSKQ queries with weight objects. Finally, the efficiency of the proposed algorithm is verified by simulation experiments.