Scinet: Interactive intent modeling for information discovery

Tuukka Ruotsalo, Jaakko Peltonen, Manuel J A Eugster, Dorota Glowacka, Aki Reijonen, Giulio Jacucci, Petri Myllymäki, Samuel Kaski

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

6 Citations (Scopus)

Abstract

Current search engines offer limited assistance for exploration and information discovery in complex search tasks. Instead, users are distracted by the need to focus their cognitive efforts on finding navigation cues, rather than selecting relevant information. Interactive intent modeling enhances the human information exploration capacity through computational modeling, visualized for interaction. Interactive intent modeling has been shown to increase task-level information seeking performance by up to 100%. In this demonstration, we showcase SciNet, a system implementing interactive intent modeling on top of a scientific article database of over 60 million documents.

Original languageEnglish
Title of host publicationSIGIR 2015 - Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval
EditorsUSA Ricardo Baeza-Yates Yahoo Labs, UK Alistair Moffat University of Melbourne Mounia Lalmas Yahoo Labs, Brazil Australia Berthier Ribeiro-Neto Google, Brazil UFMG
PublisherACM
Pages1043-1044
Number of pages2
ISBN (Print)978-1-4503-3621-5
DOIs
Publication statusPublished - 2015
MoE publication typeA4 Article in a conference publication
EventInternational ACM SIGIR Conference on Research and Development in Information Retrieval - Santiago, Chile
Duration: 9 Aug 201513 Aug 2015
Conference number: 38

Conference

ConferenceInternational ACM SIGIR Conference on Research and Development in Information Retrieval
Abbreviated titleSIGIR
CountryChile
CitySantiago
Period09/08/201513/08/2015

Keywords

  • Intent modeling
  • Interactive information retrieval
  • Personalization
  • Visual information seeking

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