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Authors: Gediminas Adomavicius 1 and Alexander Tuzhilin 2

Affiliations: 1 Carlson School of Management, University of Minnesota, United States ; 2 Stern School of Business, New York University, United States

Keyword(s): Context-aware recommender systems, collaborative filtering, rating estimation techniques.

Abstract: Traditionally recommendation technologies have been focusing on recommending items to users (or users to items) and typically do not consider additional contextual information, such as time or location. In this paper we discuss a multidimensional approach to recommender systems that supports additional dimensions capturing the context in which recommendations are made. One of the most important questions in recommender systems research is how to estimate unknown ratings, and in the paper we address this issue for the multidimensional recommendation space. We present the classification of multi- dimensional rating estimation methods, discuss how to extend traditional two-dimensional recommendation approaches to the multidimensional space, and identify research directions for the multidimensional rating estimation problem.

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Paper citation in several formats:
Adomavicius, G. and Tuzhilin, A. (2005). Incorporating Context into Recommender Systems Using Multidimensional Rating Estimation Methods. In Proceedings of the 1st International Workshop on Web Personalisation, Recommender Systems and Intelligent User Interfaces (ICETE 2005) - WPRSIUI; ISBN 972-8865-38-4, SciTePress, pages 3-13. DOI: 10.5220/0001421700030013

@conference{wprsiui05,
author={Gediminas Adomavicius. and Alexander Tuzhilin.},
title={Incorporating Context into Recommender Systems Using Multidimensional Rating Estimation Methods},
booktitle={Proceedings of the 1st International Workshop on Web Personalisation, Recommender Systems and Intelligent User Interfaces (ICETE 2005) - WPRSIUI},
year={2005},
pages={3-13},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001421700030013},
isbn={972-8865-38-4},
}

TY - CONF

JO - Proceedings of the 1st International Workshop on Web Personalisation, Recommender Systems and Intelligent User Interfaces (ICETE 2005) - WPRSIUI
TI - Incorporating Context into Recommender Systems Using Multidimensional Rating Estimation Methods
SN - 972-8865-38-4
AU - Adomavicius, G.
AU - Tuzhilin, A.
PY - 2005
SP - 3
EP - 13
DO - 10.5220/0001421700030013
PB - SciTePress

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