MnM: semi-automatic ontology population from text

Vargas-Vera, Maria; Moreale, Emanuela; Stutt, Arthur; Motta, Enrico and Ciravegna, Fabio (2007). MnM: semi-automatic ontology population from text. In: Sharman, Raj; Kishore, Rajiv and Ramesh, Ram eds. Ontologies : A Handbook of Principles, Concepts and Applications in Information Systems. Integrated Series in Information Systems (14). New York: Springer Science+Business Media, LLC, pp. 373–402.

DOI: https://doi.org/10.1007/978-0-387-37022-4_13

Abstract

Ontologies can play a very important role in information systems. They can support various information system processes, particularly information acquisition and integration. Ontologies themselves need to be designed, built and maintained. An important part of the ontology engineering cycle is the ability to keep a handcrafted ontology up to date. Therefore, we have developed a tool called MnM that helps during the ontology maintenance process. MnM extracts information from texts and populates an ontology. It uses NLP (Natural Language Processing), Information Extraction and Machine Learning technologies. In particular, MnM was tested using an electronic newsletter consisting of news articles describing events happening in the Knowledge Media Institute (KMi). MnM could constitute an important part of an ontology-driven information system, with its integrated web-based ontology editor and provision of open APIs to link to ontology servers and to integrate with information extraction tools.

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