Time-aware collective spatial keyword query

Abstract

The collective spatial keyword query is a hot research topic in the database community in recent years, which considers both the positional relevance to the query location and textual relevance to the query keywords. However, in real life, the temporal information of object is not always valid. Based on this, we define a new query, namely time-aware collective spatial keyword query (TCoSKQ), which considers the positional relevance, textual relevance, and temporal relevance between objects and query at the same time. Two evaluation functions are defined to meet different needs of users, for each of which we propose an algorithm. Effective pruning strategies are proposed to improve query efficiency based on the two algorithms. Finally, the experimental results show that the proposed algorithms are efficient and scalable.

Research on Time-Aware Group Query Method with Exclusion Keywords

“…The index can effectively prune the search space and take into account both keyword information and temporal information. Chen et al [30] proposed two evaluation functions for time-aware aggregate keyword queries to meet different types of query requirements and both proposed corresponding processing algorithms. Chan et al [31] studied the model of indoor keyword routing with time constraints, i.e., the TIKRQ problem (time-constrained indoor keyword-aware routing query), and proposed a series of pruning rules and corresponding solution algorithms.…”