Welcome to the InfoSci Platform
Ontology Learning in Practice: Using Semantics for Knowledge Grounding

Ontology Learning in Practice: Using Semantics for Knowledge Grounding

Irena Markievicz, Daiva Vitkutė-Adžgauskienė, Minija Tamošiūnaitė
Copyright: © 2014 |Pages: 14
ISBN13: 9781466661547|ISBN10: 1466661542|EISBN13: 9781466661554
DOI: 10.4018/978-1-4666-6154-7.ch009
Cite Chapter Cite Chapter

MLA

Markievicz, Irena, et al. "Ontology Learning in Practice: Using Semantics for Knowledge Grounding." E-Learning as a Socio-Cultural System: A Multidimensional Analysis, edited by Vaiva Zuzevičiūtė, et al., IGI Global, 2014, pp. 158-171. https://doi.org/10.4018/978-1-4666-6154-7.ch009

APA

Markievicz, I., Vitkutė-Adžgauskienė, D., & Tamošiūnaitė, M. (2014). Ontology Learning in Practice: Using Semantics for Knowledge Grounding. In V. Zuzevičiūtė, E. Butrimė, D. Vitkutė-Adžgauskienė, V. Vladimirovich Fomin, & K. Kikis-Papadakis (Eds.), E-Learning as a Socio-Cultural System: A Multidimensional Analysis (pp. 158-171). IGI Global. https://doi.org/10.4018/978-1-4666-6154-7.ch009

Chicago

Markievicz, Irena, Daiva Vitkutė-Adžgauskienė, and Minija Tamošiūnaitė. "Ontology Learning in Practice: Using Semantics for Knowledge Grounding." In E-Learning as a Socio-Cultural System: A Multidimensional Analysis, edited by Vaiva Zuzevičiūtė, et al., 158-171. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-6154-7.ch009

Export Reference

Mendeley
Favorite

Abstract

This chapter presents research results, showing the use of ontology learning for knowledge grounding in e-learning environments. The established knowledge representation model is organized around actions, as the main elements linking the acquired knowledge with knowledge-based real-world activities. A framework for action ontology building from domain-specific corpus texts is suggested, utilizing different Natural Language Processing (NLP) techniques, such as collocation extraction, frequency lists, word space model, etc. The suggested framework employs additional knowledge sources of WordNet and VerbNet with structured linguistic and semantic information. Results from experiments with crawled chemical laboratory corpus texts are presented.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.