Journal's Facebook pageHypothetical Tensor-based Multi-criteria Recommender System for New Users with Partial Preferences
- Western Norway Research Institute
Box 163, NO-6851 Sogndal, Norway
msh@vestforsk.no - Department of Computer Engineering Chung-Ang University
84 Heukseok-ro, Seoul, Korea
j3ung@cau.ac.kr, j2jung@gmail.com
Abstract
Multi-Criteria Recommender Systems (MCRSs) have been developed to improve the accuracy of single-criterion rating-based recommender systems that could not express and reflect users’ fine-grained rating behaviors. In most MCRSs, new users are asked to express their preferences on multi-criteria of items, to address the cold-start problem. However, some of the users’ preferences collected are usually not complete due to users’ cognitive limitation and/or unfamiliarity on item domains, which is called ‘partial preferences’. The fundamental challenge and then negatively affects to accurately recommend items according to users’ preferences through MCRSs. In this paper, we propose a Hypothetical Tensor Model (HTM) to leverage auxiliary data complemented through three intuitive rules dealing with user’s unfamiliarity. First, we find four patterns of partial preferences that are caused by users’ unfamiliarity. And then the rules are defined by considering relationships between multi-criteria. Lastly, complemented preferences are modeled by a tensor to maintain an inherent structure of and correlations between the multi-criteria. Experiments on a TripAdvisor dataset showed that HTM improves MSE performances from 40 to 47% by comparing with other baseline methods. In particular, effectivenesses of each rule regarding multi-criteria on HTM are clearly revealed.
Key words
Cold-start problem, Partial preferences, Multi-criteria recommender system, Tensor factorization
Digital Object Identifier (DOI)
https://doi.org/10.2298/CSIS200531056H
Publication information
Volume 18, Issue 1 (January 2021)
Year of Publication: 2021
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium
Full text
Available in PDF
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How to cite
Hong, M., Jung, J. J.: Hypothetical Tensor-based Multi-criteria Recommender System for New Users with Partial Preferences. Computer Science and Information Systems, Vol. 18, No. 1, 285–301. (2021), https://doi.org/10.2298/CSIS200531056H
