On Generalizing Collective Spatial Keyword Queries

Harry Kai-Ho Chan, Cheng Long, Raymond Chi-Wing Wong

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)
555 Downloads (Pure)

Abstract

With the proliferation of spatial-textual data such as location-based services and geo-tagged websites, spatial keyword queries are ubiquitous in real life. One example of spatial-keyword query is the so-called collective spatial keyword query (CoSKQ) which is to find for a given query consisting a query location and several query keywords a set of objects which covers the query keywords collectively and has the smallest cost wrt the query location. In the literature, many different functions were proposed for defining the cost and correspondingly, many different approaches were developed for the CoSKQ problem. In this paper, we study the CoSKQ problem systematically by proposing a unified cost function and a unified approach for the CoSKQ problem (with the unified cost function). The unified cost function includes all existing cost functions as special cases and the unified approach solves the CoSKQ problem with the unified cost function in a unified way. Experiments were conducted on both real and synthetic datasets which verified our proposed approach.
Original languageEnglish
Pages (from-to)1712-1726
JournalIEEE Transactions on Knowledge and Data Engineering
Volume30
Issue number9
Early online date01 Feb 2018
DOIs
Publication statusPublished - 01 Sep 2018

Keywords

  • Spatial keyword queries
  • unified framework

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

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