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Authors: Esteban García-Cuesta 1 ; Daniel Gómez-Vergel 1 ; Luis Gracias Expósito 1 and María Vela-Pérez 2

Affiliations: 1 Universidad Europea de Madrid, Spain ; 2 Universidad Complutense de Madrid, Spain

ISBN: 978-989-758-222-6

Keyword(s): User Opinion, Recommendation Systems, User Modeling, Prediction, Hyper-personalization.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Data Engineering ; Information Retrieval ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Matrix Factorization ; Natural Language Processing ; Ontologies and the Semantic Web ; Pattern Recognition ; Software Engineering ; Symbolic Systems ; Theory and Methods ; Web Applications

Abstract: The rapid proliferation of social network services (SNS) gives people the opportunity to express their thoughts, opinions, and tastes on a wide variety of subjects such as movies or commercial items. Most item shopping websites currently provide SNS systems to collect users’ opinions, including rating and text reviews. In this context, user modeling and hyper-personalization of contents reduce information overload and improve both the efficiency of the marketing process and the user’s overall satisfaction. As is well known, users’ behavior is usually subject to sparsity and their preferences remain hidden in a latent subspace. A majority of recommendation systems focus on ranking the items by describing this subspace appropriately but neglect to properly justify why they should be recommended based on the user’s opinion. In this paper, we intend to extract the intrinsic opinion subspace from users’ text reviews –by means of collaborative filtering techniques– in order to capture their tastes and predict their future opinions on items not yet reviewed. We will show how users’ reviews can be predicted by using a set of words related to their opinions. (More)

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Paper citation in several formats:
García-Cuesta, E.; Gómez-Vergel, D.; Gracias Expósito, L. and Vela-Pérez, M. (2017). Prediction of User Opinion for Products - A Bag-of-Words and Collaborative Filtering based Approach.In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-222-6, pages 233-238. DOI: 10.5220/0006209602330238

@conference{icpram17,
author={Esteban García{-}Cuesta. and Daniel Gómez{-}Vergel. and Luis Gracias Expósito. and María Vela{-}Pérez.},
title={Prediction of User Opinion for Products - A Bag-of-Words and Collaborative Filtering based Approach},
booktitle={Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2017},
pages={233-238},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006209602330238},
isbn={978-989-758-222-6},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Prediction of User Opinion for Products - A Bag-of-Words and Collaborative Filtering based Approach
SN - 978-989-758-222-6
AU - García-Cuesta, E.
AU - Gómez-Vergel, D.
AU - Gracias Expósito, L.
AU - Vela-Pérez, M.
PY - 2017
SP - 233
EP - 238
DO - 10.5220/0006209602330238

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