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Rafael Valencia-García

Researcher at University of Murcia

Publications -  208
Citations -  3276

Rafael Valencia-García is an academic researcher from University of Murcia. The author has contributed to research in topics: Ontology (information science) & Semantic Web. The author has an hindex of 27, co-authored 179 publications receiving 2740 citations. Previous affiliations of Rafael Valencia-García include Charles III University of Madrid.

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Journal ArticleDOI

Social knowledge-based recommender system. Application to the movies domain

Walter Carrer-Neto, +3 more
- 01 Sep 2012 - 
TL;DR: A hybrid recommender system based on knowledge and social networks is presented and its evaluation in the cinematographic domain yields very promising results compared to state-of-the-art solutions.
Journal ArticleDOI

Feature-based opinion mining through ontologies

Isidro Peñalver-Martinez, +6 more
- 01 Oct 2014 - 
TL;DR: This paper proposes an innovative opinion mining methodology that takes advantage of new Semantic Web-guided solutions to enhance the results obtained with traditional natural language processing techniques and sentiment analysis processes and provides a new vector analysis-based method for sentiment analysis.
Journal ArticleDOI

RecomMetz: A context-aware knowledge-based mobile recommender system for movie showtimes

Luis Omar Colombo-Mendoza, +4 more
- 15 Feb 2015 - 
TL;DR: The evaluation results show the efficiency and effectiveness of the recommendation mechanism implemented by RecomMetz in both a cold-start scenario and a no cold- start scenario.
Proceedings ArticleDOI

A Systematic Review and Comparison of Security Ontologies

Carlos Blanco, +5 more
TL;DR: This paper identifies, extracting and analyzing the main proposals for security ontologies and concludes by stating their early state of development and the need of additional research efforts.
Journal ArticleDOI

Sentiment Analysis on Tweets about Diabetes: An Aspect-Level Approach.

María del Pilar Salas-Zárate, +5 more
- 19 Feb 2017 - 
TL;DR: An aspect-level sentiment analysis method based on ontologies in the diabetes domain, which calculates the sentiment of the aspects by considering the words around the aspect which are obtained through N-gram methods.