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Authors: Sonia Ben Ticha 1 ; Azim Roussanaly 2 ; Anne Boyer 2 and Khaled Bsaïes 3

Affiliations: 1 Lorraine university and Tunis El Manar University, France ; 2 Lorraine University, France ; 3 Tunis El Manar University, Tunisia

ISBN: 978-989-758-024-6

Keyword(s): Hybrid Recommender System, Latent Semantic Analysis, Rocchio Algorithm.

Related Ontology Subjects/Areas/Topics: Enterprise Information Systems ; Recommendation Systems ; Software Agents and Internet Computing

Abstract: Recommender system provides relevant items to users from huge catalogue. Collaborative filtering and content-based filtering are the most widely used techniques in personalized recommender systems. Collaborative filtering uses only the user-ratings data to make predictions, while content-based filtering relies on semantic information of items for recommendation. Hybrid recommendation system combines the two techniques. The aim of this work is to introduce a new approach for semantically enhanced collaborative filtering. Many works have addressed this problem by proposing hybrid solutions. In this paper, we present another hybridization technique that predicts users preferences for items based on their inferred preferences for semantic information of items. For this, we design a new user semantic model by using Rocchio algorithm and we apply a latent semantic analysis to reduce the dimension of data. Applying our approach to real data, the MoviesLens 1M data set, significant improvement can be noticed compared to usage only approach, and hybrid algorithm. (More)

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Paper citation in several formats:
Ben Ticha, S.; Roussanaly, A.; Boyer, A. and Bsaïes, K. (2014). User Semantic Model for Dependent Attributes to Enhance Collaborative Filtering.In Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-024-6, pages 205-212. DOI: 10.5220/0004951102050212

@conference{webist14,
author={Sonia Ben Ticha. and Azim Roussanaly. and Anne Boyer. and Khaled Bsaïes.},
title={User Semantic Model for Dependent Attributes to Enhance Collaborative Filtering},
booktitle={Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2014},
pages={205-212},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004951102050212},
isbn={978-989-758-024-6},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - User Semantic Model for Dependent Attributes to Enhance Collaborative Filtering
SN - 978-989-758-024-6
AU - Ben Ticha, S.
AU - Roussanaly, A.
AU - Boyer, A.
AU - Bsaïes, K.
PY - 2014
SP - 205
EP - 212
DO - 10.5220/0004951102050212

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