Abstract
The collective spatial keyword query (CSKQ), an important variant of spatial keyword queries, aims to find a set of the objects that collectively cover users' queried keywords, and those objects are close to the query location and have small inter-object distances. Existing works only focus on the CSKQ problem in the Euclidean space, although we observe that, in many real-life applications, the closeness of two spatial objects is measured by their road network distance. Thus, existing methods cannot solve the problem of network-based CSKQ efficiently. In this paper, we study the problem of collective spatial keyword query processing on road networks , where the objects are located on a predefined road network. We first prove that this problem is NP-complete , and then we propose two approximate algorithms with provable approximation bounds and one exact algorithm, for supporting CSKQ on road networks efficiently. Extensive experiments using real datasets demonstrate the efficiency and accuracy of our presented algorithms.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Intelligent Transportation Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
