Research On Set-Oriented Spatial Keyword Query

Recently, set-oriented spatial keyword query is becoming research focus. The socalled set-oriented spatial keyword query is to retrieve a group of spatial web objects suchthat the group’s keywords cover the query’s keywords and such that objects are nearest tothe query location and have the lowest inter-object distances. Because the existing queriesare not very perfect and some queries have not yet been studied, so a new solution basedon TYPE3on set-oriented spatial keyword query and a solution on set-oriented spatialordered keyword query are proposed in this paper.First of all, the existing query leading to object sets with different quality have thesame the Cost value. The Cost function is used to describe the distance between q and setand the distance between two objects in the set. Based on it, a new Cost function isproposed. In this function, the distance between q and the center of the smallest circleenclosing the object set is used to describe the distance between q and the object set, andthe diameter of the smallest circle is used to describe the density of the object set. Aneffective pruning strategy is used to end the query earlier, and an approximate algorithmand an exact algorithm are both proposed.Second, the existing query can not resolve the set-oriented spatial keyword querywhen the keywords are ordered, so we put forward the corresponding solution. Based onthis, set-oriented spatial ordered keyword query is proposed in this paper. On the basis ofthe existing query, the concept of decomposition of the keyword set is used to deal withordered keywords. A plain approximation algorithm and an optimized approximationalgorithm based on incremental thinking are proposed.Finally, a comprehensive experimental evaluation using real dataset has beenconducted to demonstrate the efficiency and effectiveness of our proposed algorithms.