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User involvement in automatic filtering: an experimental study
RISE, Swedish ICT, SICS.
2004 (English)In: User modeling and user-adapted interaction, ISSN 0924-1868, E-ISSN 1573-1391, Vol. 14, no 2-3, 201-237 p.Article in journal (Refereed) Published
Abstract [en]

The aim in information filtering is to provide users with a personalised selection of information, based on their interest profile. In adaptive information filtering, this profile partially or completely acquired by automatic means. This paper investigates if profile generation can be partially acquired by automatic methods and partially by direct user involvement. The issue is explored through an empirical study of a simulated filtering system that mixes automatic and manual profile generation. The study covers several issues involved in mixed control. The first issue concerns if a machine-learned profile can provide better filtering performance if generated from an initial explicit user profile. The second issue concerns if user involvement can improve on a system-generated or adapted profile. Finally, the relationship between filtering performance and user ratings is investigated. In this particular study the initial setup of a personal profile was effective and yielded performance improvements that persisted after substantiate training. However, the study showed no correlation between users’ ratings of profiles and profile filtering performance, and only weak indications that users could improve profiles that already had been trained on feedback.

Place, publisher, year, edition, pages
2004, 1. Vol. 14, no 2-3, 201-237 p.
Keyword [en]
experimental study - information filtering - personal profile - recommender systems - user involvement
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:ri:diva-22322DOI: 10.1023/B:USER.0000028984.13876.9bOAI: oai:DiVA.org:ri-22322DiVA: diva2:1041867
Available from: 2016-10-31 Created: 2016-10-31 Last updated: 2017-08-10Bibliographically approved

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