时间：2018年4月24日11：00
地点：旗山校区数信大楼507
主讲：丹麦奥尔堡大学 郑渤龙博士后
主办：数学与信息学院
专家简介：郑渤龙，1989年11月生，2017年3月获澳大利亚昆士兰大学博士学位，现任职于丹麦奥尔堡大学，从事博士后研究。研究兴趣包括时空数据库、数据挖掘、文本语义分析、轨迹数据分析与挖掘和社交网络查询与挖掘。其主要科研成果已先后发表在SIGMOD、VLDB、ICDE、WWW、TKDE、CIKM、DASFAA、WWWJ等国际顶级学术期刊和会议上。担任DASFAA、MDM、CIKM、APWeb国际学术会议PC Member；担任TKDE、VLDBJ、ACM TIST、WWWJ、KAIS、Neurocomputing、JCST等国际期刊审稿人。
报告摘要：With the advances in geo-positioning technologies and location-based services, it is nowadays quite common for road networks to have textual contents on the vertices. Previous work on identifying an optimal route that covers a sequence of query keywords has been studied in recent years. However, in many practical scenarios, an optimal route might not always be desirable. For example, a personalized route query is issued by providing some clues that describe the spatial context between PoIs along the route, where the result can be far from the optimal one. Therefore, in this paper, we investigate the problem of clue-based route search (CRS), which allows a user to provide clues on keywords and spatial relationships. First, we propose a greedy algorithm and a dynamic programming algorithm as baselines. To improve efficiency, we develop a branch-and-bound algorithm that prunes unnecessary vertices in query processing. In order to quickly locate candidate, we propose an AB-tree that stores both the distance and keyword information in tree structure. To further reduce the index size, we construct a PB-tree by utilizing the virtue of 2-hop label index to pinpoint the candidate. Extensive experiments are conducted and verify the superiority of our algorithms and index structures.