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Comprehensive Evaluation of Matrix Factorization Models for Collaborative Filtering Recommender Systems
Matrix factorization models are the core of current commercial collaborative filtering Recommender Systems. This paper tested six representative matrix factorization models, using four collaborative filtering datasets. ...
Group recommendation strategies based on collaborative filtering
(Universidade Federal de Pernambuco, 2014)
Personalized collaborative filtering: a neighborhood model based on contextual constraints
(Association for Computing Machinery - ACMDongguk UniversityGyeongju, 2014-03)
In this paper, we propose a recommender system approach which considers contextual information from users and items in order to improve the accuracy of a neighborhood-based collaborative filtering algorithm. One advantage ...
A sentiment-based item description approach for kNN collaborative filtering
(Association for Computing Machinery - ACMUniversity of SalamancaSalamanca, 2015-04)
In this paper, we propose an approach based on sentiment analysis to describe items in a neighborhood-based collaborative filtering model. We use unstructured users' reviews to produce a vector-based representation that ...
Regularização social em sistemas de recomendação com filtragem colaborativa
(Universidade Federal de São CarlosUFSCarPrograma Interinstitucional de Pós-Graduação em Ciências Fisiológicas - PIPGCFCâmpus São Carlos, 2019-05-14)
Models based on matrix factorization are among the most successful implementations of Recommender Systems. In this project, we study the possibilities of incorporating the information
from social networks to improve the ...
Neural Collaborative Filtering Classification Model to Obtain Prediction Reliabilities
Neural collaborative filtering is the state of art field in the recommender systems area; it provides some models that obtain accurate predictions and recommendations. These models are regression-based, and they just
return ...
Deep learning techniques for recommender systems based on collaborative filtering
(Wiley-Blackwell, 2020-11-14)
In the Big Data Era, recommender systems perform a fundamental role in data management and information filtering. In this context, Collaborative Filtering (CF) persists as one of the most prominent strategies to effectively ...
An Adapted Approach for User Profiling in a Recommendation System: Application to Industrial Diagnosis
In this paper, we propose a global architecture of a recommender tool, which represents a part of an existing collaborative platform. This tool provides diagnostic documents for industrial operators. The recommendation ...
Sistema de recomendación de Recreovías, utilizando un modelo híbrido de Collaborative Filtering, Demographic Correlation y Content-Based FilteringSistema de recomendación de Recreovías, utilizando un modelo híbrido de Collaborative Filtering, Demographic Correlation y Content-Based Filtering
(UniandesUniandesIngeniería ElectrónicaIngeniería ElectrónicaFacultad de IngenieríaFacultad de IngenieríaDepartamento de Ingeniería Eléctrica y ElectrónicaDepartamento de Ingeniería Eléctrica y Electrónica, 2016)