Beyond Relevance: Adapting Exploration/Exploitation in Information Retrieval

Kumaripaba Athukorala, Alan Medlar, Antti Oulasvirta, Giulio Jacucci, Dorota Glowacka

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

Abstract

We present a novel adaptation technique for search engines to better support information-seeking activities that include both lookup and exploratory tasks. Building on previous findings, we describe (1) a classifier that recognizes task type (lookup vs. exploratory) as a user is searching and (2) a reinforcement learning based search engine that adapts accordingly the balance of exploration/exploitation in ranking the documents. This allows supporting both task types surreptitiously without changing the familiar list-based interface. Search results include more diverse results when users are exploring and more precise results for lookup tasks. Users found more useful results in exploratory tasks when compared to a base-line system, which is specifically tuned for lookup tasks.
Original languageEnglish
Title of host publicationProceedings of the 21st International Conference on Intelligent User Interfaces
Place of PublicationNew York, NY, USA
PublisherACM
Pages359-369
Number of pages11
ISBN (Print)978-1-4503-4137-0
DOIs
Publication statusPublished - Mar 2016
Event 21st International Conference on Intelligent User Interfaces - Sonoma, United States
Duration: 7 Mar 201610 Mar 2016
http://iui.acm.org/2016/

Publication series

NameIUI '16
PublisherACM

Conference

Conference 21st International Conference on Intelligent User Interfaces
Abbreviated titleIUI 2016
CountryUnited States
CitySonoma
Period7/03/1610/03/16
Internet address

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