Concept Discovery through Information Extraction in Restaurant Domain

• Autores: Nadeesha Pathirana, Sandaru Seneviratne, Rangika Samarawickrama, Shane Wolff, Charith Chitraranjan, Uthayasanker Thayasivam, Tharindu Ranasinghe
• Localización: Computación y Sistemas (CyS), ISSN 1405-5546, ISSN-e 2007-9737, Vol. 23, Nº. 3, 2019, págs. 741-749
• Idioma: inglés
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• Resumen

  • Abstract Concept identification is a crucial step in understanding and building a knowledge base for any particular domain. However, it is not a simple task in very large domains such as restaurants and hotel. In this paper, a novel approach of identifying a concept hierarchy and classifying unseen words into identified concepts related to restaurant domain is presented. Sorting, identifying, classifying of domain-related words manually is tedious and therefore, the proposed process is automated largely. Word embedding, hierarchical clustering, classification algorithms are effectively used to obtain concepts related to the restaurant domain. Further, this approach can also be extended to create a semi-automatic ontology on restaurant do-main.