Visual Re-Ranking for Multi-Aspect Information Retrieval

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Details

Original languageEnglish
Title of host publicationCHIIR 2017 - Proceedings of the 2017 Conference Human Information Interaction and Retrieval
Place of PublicationNew York
PublisherACM
Pages57-66
Number of pages10
ISBN (Electronic)978-1-4503-4677-1
StatePublished - 2017
MoE publication typeA4 Article in a conference publication
EventConference on Human Information Interaction and Retrieval - Oslo, Norway
Duration: 7 Mar 201711 Mar 2017
Conference number: 2
http://sigir.org/chiir2017/

Conference

ConferenceConference on Human Information Interaction and Retrieval
Abbreviated titleCHIIR
CountryNorway
CityOslo
Period07/03/201711/03/2017
Internet address

Researchers

Research units

  • University of Helsinki

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 reranking 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.

    Research areas

  • information visualization, information retrieval, multi-aspect search, multi-dimensional ranking

ID: 11782342