在线位置服务技术日益普及,用户能够很容易获得他们的地理位置信息.随之产生了各类有关空间关键字的查询,这些查询可以提供定位服务的基本查询功能.研究了基于位置的偏好查询处理技术,旨在为用户找到一个目的地,找到的结果应该满足指定的特性,并且靠近满足用户提出的偏好.同时,提出一种新颖的查询框架,该框架通过对IR-tree的节点扩展给出预计算信息表,根据扩展的IR-tree能够减少搜索空间并提出准确计算方法来有效地回答基于位置的偏好查询.在真实数据集上进行实验验证了提出方法的有效性.
There has been increasing popularity of online location-based services. It gives prominence to various types of spatial-keyword queries, which are employed to provide fundamental querying functionality for location-based services. A technique for processing location-aware preference queries was studied that aimed to find a destination place for a user. The user wants to go to a place labeled with a specified category feature (e. g., hotel),and he/she has a location and a set of additional preferences. It was expected that the result place of the query belongs to the specified feature, and it was close to places satisfying the preferences of the user. A novel framework was developed for answering the queries,which was called augmented IR- tree. An augmented IR-tree could be obtained by adding the pre-computed information into an IR- tree. The augmented IR-tree could be used to reduce the search space and compute the exact query result. The proposed technique was verified by extensive experiments on one real dataset, and the technique is more efficient than baseline methods.