Interpreting user inaction in recommender systems

Qian Zhao, Martijn C. Willemsen, Gediminas Adomavicius, F. Maxwell Harper, Joseph A. Konstan

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

10 Citaten (Scopus)


Temporally, users browse and interact with items in recommender systems. However, for most systems, the majority of the displayed items do not elicit any action from users. In other words, the user-system interaction process includes three aspects: browsing, action, and inaction. Prior recommender systems literature has focused more on actions than on browsing or inaction. In this work, we deployed a ield survey in a live movie recommender system to interpret what inaction means from both the user's and the system's perspective, guided by psychological theories of human decision making. We further systematically study factors to infer the reasons of user inaction and demonstrate with oline data sets that this descriptive and predictive inaction model can provide beneits for recommender systems in terms of both action prediction and recommendation timing.

Originele taal-2Engels
TitelRecSys 2018 - 12th ACM Conference on Recommender Systems
Plaats van productieNew York
UitgeverijAssociation for Computing Machinery, Inc
Aantal pagina's9
ISBN van elektronische versie9781450359016
ISBN van geprinte versie978-1-4503-5901-6
StatusGepubliceerd - 27 sep 2018
Evenement12th ACM Conference on Recommender Systems, RecSys 2018 - Vancouver, Canada
Duur: 2 okt 20187 okt 2018


Congres12th ACM Conference on Recommender Systems, RecSys 2018


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