Manuel José Barranco García

Contact

barranco@ujaentqEnMzlIs9kO.es

Organization

UJA

Researcher Profile

Total From 2019:
Citas Total: 848 From 2019: 282
Índice H Total: 12 From 2019: 8
Índice i10 Total: 12 From 2019: 6

Papers (29)

Title Authors Year
A Big Data Semantic Driven Context Aware Recommendation Method MJ Barranco, PJ Sanchez, J Castro, R Yera. 2020
Exploring Fuzzy Rating Regularities for Managing Natural Noise in Collaborative Recommendation R Yera, MJ Barranco, AA Alzahrani, L Martínez. 2019
A Big Data Semantic Driven Context Aware Recommendation Method for Question-Answer Items J Castro, RY Toledo, AA Alzahrani, PJ Sánchez, MJ Barranco, L Martínez. 2019
Group recommendations based on hesitant fuzzy sets J Castro, MJ Barranco, RM Rodríguez, L Martínez. 2018
Dealing with diversity and novelty in group recommendations using Hesitant fuzzy sets J Castro, MJ Barranco, RM Rodríguez, L Martínez. 2017
Weighting of features in content-based filtering with entropy and dependence measures J Castro, RM Rodriguez, MJ Barranco. 2014
Improving group recommendation with outlier data filtering J Castro, MJ Barranco, L Martınez. 2014
A mobile 3D-GIS hybrid recommender system for tourism JM Noguera, MJ Barranco, RJ Segura, L MartíNez. 2012
A context-aware mobile recommender system based on location and trajectory MJ Barranco, JM Noguera, J Castro, L Martínez. 2012
A Location-Aware Tourism recommender system based on mobile devices JM Noguera, MJ Barranco, RJ Segura, L Martínez. 2012
Academic Orientation Supported by Hybrid Intelligent Decision Support System EJ Castellano, MJ Barranco, L Martínez. 2011
Auto-entrenamiento y auto-evaluación a través de juegos educativos M Espinilla, I Palomares, F Mata, RM Rodríguez, A Aguilera, L Martínez, .... 2010
A method for weighting multi-valued features in content-based filtering M Barranco, L Martínez. 2010
A linguistic framework for collaborative and knowledge-based filtering: How to refine collaborative filtering recommendations MJ Barranco, LG Pérez, L Martınez. 2010
Incomplete preference relations to smooth out the cold-start in collaborative recommender systems L Martinez, LG Perez, MJ Barranco. 2009
A knowledge based recommender system with multigranular linguistic information L Martinez, MJ Barranco, LG Pérez, M Espinilla. 2008
Improving the effectiveness of knowledge based recommender systems using incomplete linguistic preference relations L MartINezt, LG Perez, M Barranco, M Espinilla. 2008
A knowledge based recommender system based on consistent preference relations L Martínez, LG Pérez, MJ Barranco, M Espinilla. 2008
A Knowledge Based Recommender System with Multigranular Hierarchical Linguistic Contexts L Martínez, MJ Barranco, LG Pérez, M Espinilla, EJ Castellano. 2008
Special issue on fuzzy approaches in preference modelling, decision making and applications F Chiclana, E Herrera-Viedma, S Alonso, F Herrera, J Yañez, J Montero, .... 2008
REJA: un sistema de recomendación de restaurantes basado en técnicas difusas MJ Barranco, LG Perez, F Mata, L Martinez. 2008
Exploiting liguistic preference relations in knowledge based recommendation systems,” LG Pérez, M Barranco, L Martınez, M Espinilla. 2007
A multigranular linguistic content‐based recommendation model L Martínez, LG Pérez, M Barranco. 2007
Building user profiles for recommender systems from incomplete preference relations LG Perez, M Barranco, L Martinez. 2007
Recomendación de perfiles académicos mediante algoritmos colaborativos basados en el expediente EJ Castellano, L Martínez, M Barranco, LG PÉREZ. 2007
Un sistema de recomendación basado en conocimiento con información lingüística multigranular M Barranco, LG Pérez, L Martínez. 2006
Un modelo de recomendación con perfiles de usuario lingüísticos LG Pérez, L Martınez, F Mata, M Barranco. 2004

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