SWORS: a system for the efficient retrieval of relevant spatial web objects

  • Authors:
  • Xin Cao;Gao Cong;Christian S. Jensen;Jun Jie Ng;Beng Chin Ooi;Nhan-Tue Phan;Dingming Wu

  • Affiliations:
  • Nanyang Technological University, Singapore;Nanyang Technological University, Singapore;Arhus University, Denmark;Nanyang Technological University, Singapore;National University of Singapore, Singapore;Nanyang Technological University, Singapore;Hongkong Baptist University, Hong Kong

  • Venue:
  • Proceedings of the VLDB Endowment
  • Year:
  • 2012

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Abstract

Spatial web objects that possess both a geographical location and a textual description are gaining in prevalence. This gives prominence to spatial keyword queries that exploit both location and textual arguments. Such queries are used in many web services such as yellow pages and maps services. We present SWORS, the Spatial Web Object Retrieval System, that is capable of efficiently retrieving spatial web objects that satisfy spatial keyword queries. Specifically, SWORS supports two types of queries: a) the location-aware top-k text retrieval (LkT) query that retrieves k individual spatial web objects taking into account query location proximity and text relevancy; b) the spatial keyword group (SKG) query that retrieves a group of objects that cover the query keywords and are nearest to the query location and have the shortest inter-object distances. SWORS provides browser-based interfaces for desktop and laptop computers and provides a client application for mobile devices. The interfaces and the client enable users to formulate queries and view the query results on a map. The server side stores the data and processes the queries. We use three real-life data sets to demonstrate the functionality and performance of SWORS.