Ontology-based information extraction and reservoir computing for topic detection from blogosphere's content : a case study about BBC backstage

Arguello-Casteleiro, M; Fernandez-Prieto, MJ

Abstract

This research study aims at detecting topics and extracting themes(subtopics) from the blogosphere’s content while bridging the gap between the Social Web and the Semantic Web. The goal is to detect certain types of information from collections of blogs’ and microblogs’ narratives that lack explicit semantics. The approach presented introduces a novel approach that blends together two young paradigms: Ontology-Based Information Extraction (OBIE) and Reservoir Computing (RC). The novelty of the work lies in integrating ontologies and RC as well as the pioneering use of RC with social media data. Experiments with retrospect data from blogs and Twitter microblogs provide valuable insights into the BBC Backstage initiative and prove the viability of the approach presented in terms of scalability, computational complexity,and performance.

Citation

Arguello-Casteleiro, M., & Fernandez-Prieto, M. (2014). Ontology-based information extraction and reservoir computing for topic detection from blogosphere's content : a case study about BBC backstage. In M. Bramer, & M. Petridis (Eds.), Research and Development in Intelligent Systems XXXI : Incorporating Applications and Innovations in Intelligent Systems XXII (333-338). Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-319-12069-0_24

• Publication Date: Dec 1, 2014
• Deposit Date: Jun 17, 2015
• Pages: 333-338
• Series Title: Research and Development in Intelligent Systems
• Book Title: Research and Development in Intelligent Systems XXXI : Incorporating Applications and Innovations in Intelligent Systems XXII
• ISBN: 9783319120690
• DOI: https://doi.org/10.1007/978-3-319-12069-0_24
• Publisher URL: http://dx.doi.org/10.1007/978-3-319-12069-0_24
• Related Public URLs: http://www.springer.com/us/book/9783319120683