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Scinet: Interactive intent modeling for information discovery

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

Details

Original languageEnglish
Title of host publicationSIGIR 2015 - Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval
PublisherAssociation for Computing Machinery, Inc
Pages1043-1044
Number of pages2
ISBN (Electronic)9781450336215
DOIs
Publication statusPublished - 9 Aug 2015
Publication typeA4 Article in a conference publication
Event38th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2015 - Santiago, Chile
Duration: 9 Aug 201513 Aug 2015

Conference

Conference38th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2015
CountryChile
CitySantiago
Period9/08/1513/08/15

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.

ASJC Scopus subject areas

Keywords

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