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ConceptMap: A Conceptual Approach for Formulating User Preferences in Large Information Spaces

  • Alireza TabebordbarEmail author
  • Amin Beheshti
  • Boualem Benatallah
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11881)

Abstract

In a large information space a user needs to iteratively investigate the data to formulate her preferences for IR systems. In recent years several visualization techniques have been proposed to help a user to better formulate her preferences. However, using these solutions a user needs to explicitly specify her preferences for IR systems in forms of keywords or phrases. In this paper we present ConceptMap, a system that takes the advantage of deep learning and a knowledge lake to provide a conceptual summary of the information space. ConceptMap allows a user to specify her preferences implicitly as a set of concepts without the need to iteratively investigate the information space. It provides a 2D Radial Map of concepts where a user can rank items relevant to her preferences through dragging and dropping. Our experiment results shows that ConceptMap can help users to better formulate their preferences when they need to retrieve varied and comprehensive list of information across a large amount of data.

Keywords

Formulating user preferences Conceptual visual summary Conceptual information retrieval 

Notes

Acknowledgements

We Acknowledge the AI-enabled Processes (AIP) Research Centre for funding part of this research.

We Acknowledge the Data to Decisions CRC (D2D CRC) and the Cooperative Research Centres Program for funding part of this research.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Alireza Tabebordbar
    • 1
    Email author
  • Amin Beheshti
    • 2
  • Boualem Benatallah
    • 1
  1. 1.University of New South WalesSydneyAustralia
  2. 2.Macquarie UniversitySydneyAustralia

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