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Visual Re-Ranking for Multi-Aspect Information Retrieval

Published: 07 March 2017 Publication History

Abstract

We present visual re-ranking, an interactive visualization technique for multi-aspect information retrieval. In multi-aspect search, the information need of the user consists of more than one aspect or query simultaneously. While visualization and interactive search user interface techniques for improving user interpretation of search results have been proposed, the current research lacks understanding on how useful these are for the user: whether they lead to quantifiable benefits in perceiving the result space and allow faster, and more precise retrieval. Our technique visualizes relevance and document density on a two-dimensional map with respect to the query phrases. Pointing to a location on the map specifies a weight distribution of the relevance to each of the query phrases, according to which search results are re-ranked. User experiments compared our technique to a uni-dimensional search interface with typed query and ranked result list, in perception and retrieval tasks. Visual re-ranking yielded improved accuracy in perception, higher precision in retrieval and overall faster task execution. Our findings demonstrate the utility of visual re-ranking, and can help designing search user interfaces that support multi-aspect search.

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Published In

cover image ACM Conferences
CHIIR '17: Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval
March 2017
454 pages
ISBN:9781450346771
DOI:10.1145/3020165
  • Conference Chairs:
  • Ragnar Nordlie,
  • Nils Pharo,
  • Program Chairs:
  • Luanne Freund,
  • Birger Larsen,
  • Dan Russel
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 07 March 2017

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Author Tags

  1. information retrieval
  2. information visualization
  3. multi-aspect search
  4. multi-dimensional ranking

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  • FP7

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CHIIR '17 Paper Acceptance Rate 10 of 48 submissions, 21%;
Overall Acceptance Rate 55 of 163 submissions, 34%

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