The paper presents the result on cross-representation mediation of user models in the context of movie recommendation. We analyze the possibility of initializing the user models for a content-based recommender starting from movie ratings provided by users in other social applications. We focus in particular on (i) an approach for inferring user model preferences from rating and (ii) the experimentation of several methods to solve the missing value problem exploiting community-based ratings. We tested different variations of the proposed approach exploiting a subset of the MovieLens 10M Dataset, computing rating predictions, and MAE.

An experimental study in cross-representation mediation of user models

CENA, Federica;GENA, Cristina;PICARDI, Claudia
2016

Abstract

The paper presents the result on cross-representation mediation of user models in the context of movie recommendation. We analyze the possibility of initializing the user models for a content-based recommender starting from movie ratings provided by users in other social applications. We focus in particular on (i) an approach for inferring user model preferences from rating and (ii) the experimentation of several methods to solve the missing value problem exploiting community-based ratings. We tested different variations of the proposed approach exploiting a subset of the MovieLens 10M Dataset, computing rating predictions, and MAE.
24th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2016
HALIFAX - CANADA
July 13 - 17, 2016
UMAP 2016 - Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization
Association for Computing Machinery, Inc
289
290
9781450343701
9781450343701
http://dl.acm.org/citation.cfm?doid=2930238.2930263
Content-based recommender systems; Cross-representation mediation of user models; Movie recommendation; Software
Cena, Federica; Gena, Cristina; Picardi, Claudia
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/1615694
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