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Maximizing Influence of Spatio-Textual Objects Based on Keyword Selection

  • Orestis GkorgkasEmail author
  • Akrivi Vlachou
  • Christos Doulkeridis
  • Kjetil Nørvåg
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9239)

Abstract

In modern applications, spatial objects are often annotated with textual descriptions, and users are offered the opportunity to formulate spatio-textual queries. The result set of such a query consists of spatio-textual objects ranked according to their distance from a desired location and to their textual relevance to the query. In this context, a challenging problem is how to select a set of at most b keywords to enhance the description of the facilities of a spatial object, in order to make the object appear in the top-k results of as many users as possible. In this paper, we formulate this problem, called Best-terms and we show that it is NP-hard. Hence, we present a baseline algorithm that provides an approximate solution to the problem. Then, we introduce a novel algorithm for keyword selection that greatly improves the efficiency of query processing. By means of a thorough experimental evaluation, we demonstrate the performance gains attained by our approach.

Keywords

User Preference Textual Description Query Point Graph Construction Inverted Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

A. Vlachou was supported by the Action “Supporting Postdoctoral Researchers” of the Operational Program “Education and Lifelong Learning” (Action’s Beneficiary: General Secretariat for Research and Technology), and is co-financed by the European Social Fund (ESF) and the Greek State. C. Doulkeridis has been co-financed by ESF and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF) - Research Funding Program: Aristeia II, Project: ROADRUNNER.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Orestis Gkorgkas
    • 1
    Email author
  • Akrivi Vlachou
    • 1
    • 2
  • Christos Doulkeridis
    • 3
  • Kjetil Nørvåg
    • 1
  1. 1.Norwegian University of Science and Technology (NTNU)TrondheimNorway
  2. 2.Institute for the Management of Information Systems, R.C. “Athena”MarousiGreece
  3. 3.Department of Digital SystemsUniversity of PiraeusPiraeusGreece

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