Observatorio de I+D+i UPM
• ESPAÑOL
• ENGLISH
INVESTIGADORES
ESTRUCTURAS DE I+D+I
ACTIVIDAD INVESTIGADORA
INNOVACIÓN
Investigador
Jesus Bobadilla Sancho
Categoría Investigador
CATEDRATICO UNIVERSIDAD
Escuela UPM
E.T.S DE ING. DE SISTEMAS INFORMÁTICOS
Departamento:
SISTEMAS INFORMÁTICOS (N)
Area Conocimiento
CC. DE COMPUTACION E INTELIGENCIA ARTIFICIAL
Grupo de Investigación:
KNOwledge Discovery and Information Systems (KNODIS)
Email (Directorio UPM)
jesus.bobadilla
upm.es
Teléfono (Directorio UPM)
910673644
Datos de Memorias relacionados
Proyectos de I+D+i y generación de recursos
9 Proyectos de I+D+i
1: (2008)
Investigación y Desarrollo de Sistemas de Recomendación
2: (2009)
AMPLIACION Y EVOLUCION DE UN SISTEMA DE RECOMENDACION DE PELICULAS
3: (2009)
INVESTIGACIÓN Y DESARROLLO DE SISTEMAS DE RECOMENDACIÓN.
4: (2010)
COMUNICACIONES EN MALLA PARA VEHICULOS E INFRAESTRUCTURAS INTELIGENTES
5: (2010)
COMUNICACIONES ENTRE VEHICULOS E INFRAESTRUTURAS (V2V Y V2I) BASADOS EN REDES EN MALLA PARA SISTEMAS INTELIGENTES DE TRANSPORTE
6: (2011)
Comunicaciones en malla para vehículos e infraestructuras inteligentes
7: (2012)
Comunicaciones en malla para vehiculos e infraestructuras inteligentes.
8: (2013)
Aumento de Prestaciones en los Sistemas de Recomendación Basados en Filtrado Colaborativo
9: (2015)
SIREFICO: Aumento de prestaciones en los sistemas de recomendación basados en filtrado colaborativo
Formación de Investigadores y Movilidad
1 Tesis Doctorales
1: (2015)
Incorporating Group Recommendations to Recommender Systems: Alternatives and Performance
Difusión de Resultados de Investigación
44 Artículos en revistas
1: (2009)
Collaborative Filtering adapted to Recommender Systems of E-Learning
2: (2010)
A new collaborative filtering metric that improves the behavior of recommender systems
3: (2011)
A framework for collaborative filtering recommender systems
4: (2011)
A framework for collaborative filtering recommender systems
5: (2011)
Extended precision quality measure for recommender systems
6: (2011)
Improving collaborative filtering recommender system results and performance using genetic algorithms
7: (2012)
A Balanced Memory-Based Collaborative Filtering Similarity Measure
8: (2012)
A collaborative filtering approach to mitigate the new user cold start problem
9: (2012)
A collaborative filtering approach to mitigate the new user cold start problem
10: (2012)
A collaborative filtering similarity measure based on singularities
11: (2012)
Collaborative Filtering Based on Significances
12: (2012)
Collaborative filtering based on significances
13: (2012)
Generalization of Recommender Systems: Collaborative Filtering Extended to Group of Users and Restricted to Groups of Items
14: (2012)
Generalization of recommender systems: Collaborative filtering extended to groups of users and restricted to groups of items
15: (2013)
A similarity metric designed to speed up, using hardware, the recommender systems k-nearest neighbors algorithm
16: (2013)
A similarity metric designed to speed up, using hardware, the recommender systems k-nearest neighbors algorithm
17: (2013)
Hierarchical graph maps for visualization of collaborative recommender systems
18: (2013)
Improving collaborative filtering-based recommender systems results using Pareto dominance
19: (2013)
Improving collaborative filtering-based recommender systems results using Pareto dominance
20: (2013)
Incorporating group recommendations to recommender systems: Alternatives and performance
21: (2013)
Incorporating reliability measurements into the predictions of a recommender system
22: (2013)
Recommender systems survey
23: (2013)
Trees for explaining recommendations made through collaborative filtering
24: (2014)
Hierarchical graph maps for visualization of collaborative recommender systems
25: (2014)
Using Hierarchical Graph Maps to Explain Collaborative Filtering Recommendations
26: (2016)
A non negative matrix factorization for collaborative filtering recommender systems based on a Bayesian probabilistic model
27: (2016)
Recommending items to group of users using Matrix Factorization based Collaborative Filtering
28: (2017)
A Novel Asymmetric Semantic Similarity Measurement for Semantic Job Matching
29: (2017)
A probabilistic model for recommending to new cold-start non-registered users
30: (2017)
Recommender Systems Clustering Using Bayesian Non Negative Matrix Factorization
31: (2018)
A New Recommendation Approach Based on Probabilistic Soft Clustering Methods: A Scientific Documentation Case Study
32: (2018)
An efficient recommender system method based on the numerical relevances and the non-numerical structures of the ratings
33: (2018)
Artificial Intelligence Scientific Documentation Dataset for Recommender Systems
34: (2018)
Assigning reliability values to recommendations using matrix factorization
35: (2018)
CF4J: Collaborative Filtering for Java
36: (2018)
Method to interactively visualize and navigate related information
37: (2018)
Recommendation to Groups of Users Using the Singularities Concept
38: (2018)
Recommender Systems Clustering Using Bayesian Non Negative Matrix Factorization
39: (2018)
Reliability quality measures for recommender systems
40: (2018)
VisualRS: Java framework for visualization of recommender systems information
41: (2019)
A Hybrid Approach of Recommendation via Extended Matrix Based on Collaborative Filtering with Demographics Information
42: (2019)
A New Recommendation Approach Based on Probabilistic Soft Clustering Methods: A Scientific is Documentation Case Study
43: (2019)
Analysis of scientific production based on trending research topics. An Artificial Intelligence case study
44: (2019)
Robust Model-Based Reliability Approach to Tackle Shilling Attacks in Collaborative Filtering Recommender Systems
3 Capítulos de libros
1: (2008)
Applications of Formant Detection in Language Learning
2: (2009)
Reducing Recommender Systems Data Base Sizes and Improving their Accuracy
3: (2010)
Collaborative Filtering Based on Choosing a Different Number of Neighbors for Each User
5 Ponencia en Congresos
1: (2007)
Mapaci: A Real Time e-Health Application to Assist Throat Complaint Patients
2: (2008)
Choice of Metrics used in Collaborative Filtering and their Impact on Recommender Systems
3: (2009)
Recommender Systems: Improving Collaborative Filtering Results
4: (2009)
Reducing Recommender Systems Data Base Sizes and Improving their accuracy
5: (2009)
The Incidence of Sparsity on Collaborative Filtering Metrics
Explotación de Resultados y Transferencia de Tecnología
1 Know-How
1: (2016)
Cátedra UPM: BigTrueData I+D sobre Machine Learning
1 Patentes
1: (2009)
Sistema Telemático de emparejamiento entre ofertantes y demandantes, basado en el uso de los protocolos de correo electrónico
1 Registros de Software
1: (2009)
Aplicación Avanzada de Filtrado Colaborativo
• TOMA DE DATOS DE MEMORIAS Y CV
• UPM.ES
S2i 2022 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
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