考虑可达性的Top-k空间关键词查询

Top-k spatial keyword query based on reachability

空间关键词查询(SKQ)是时空数据库领域的研究热点,查询同时考虑查询点与空间-文本对象之间的空间邻近度和文本相似性,这一技术在现实生活中的应用非常广泛.为了更好地满足用户的个性化需求,提高空间关键词查询的精确性和实时性,提出了考虑可达性的Top-k空间关键词查询(RSKQ).该查询返回满足可达性和查询关键词约束、考虑了查询和对象之间空间邻近度、文本相似性和可达性的综合得分最优的k个对象.首先基于真实的路网信息和历史轨迹数据建立综合索引SRTR-Tree,设计了有效的算法计算由查询点到对象的可达概率并进行RSKQ查询处理;然后设计了3种剪枝技术加快查询处理的速度,返回k个满足要求的最优结果;最后通过实验验证了算法的有效性.

Spatial keyword query(SKQ)is a research hotspot in the field of spatio-temporal databases and takes into account the spatial proximity and text similarity between the query and spatio-textual objects.This technology is widely used in real life.In order to better meet the personalized needs of users and improve the accuracy and real-time of the spatial keyword query,the Top-k spatial keyword query based on reachability(RSKQ)is proposed.Such query returns the k best objects that satisfy the reachability and query keyword constraints according to a comprehensive score,which considers the spatial proximity,text similarity,and reachability between the query and the object.Firstly,a comprehensive index named SRTR-Tree based on the real road network information and historical trajectory data is established and effective algorithms for calculating the reachable probability from the query to objects and processing RSKQ query are designed.Secondly,three pruning techniques are designed to speed up query processing and k optimal results that meet query requirements are returned.Finally,the effectiveness of the algorithm is verified by experiments.