Concept Discovery through Information Extraction in Restaurant Domain

Authors

  • Nadeesha Pathirana University of Moratuwa, Faculty of Engineering, Department of Computer Science and Engineering
  • Sandaru Seneviratne University of Moratuwa, Faculty of Engineering, Department of Computer Science and Engineering
  • Rangika Samarawickrama University of Moratuwa, Faculty of Engineering, Department of Computer Science and Engineering
  • Shane Wolff University of Moratuwa, Faculty of Engineering, Department of Computer Science and Engineering
  • Charith Chitraranjan University of Moratuwa, Faculty of Engineering, Department of Computer Science and Engineering
  • Uthayasanker Thayasivam University of Moratuwa, Faculty of Engineering, Department of Computer Science and Engineering
  • Tharindu Ranasinghe CodeGen International, Trace Expert City

DOI:

https://doi.org/10.13053/cys-23-3-3277

Keywords:

Word embedding, word2vec, gloVe, hierarchical clustering

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 to a great extent. 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 domain.

Downloads

Published

2019-09-25

Issue

Vol. 23 No. 3 (2019): Thematic issue: Computational Linguistics (Guest Editor A. Gelbukh)

Section

Articles of the Thematic Issue

License 

Hereby I transfer exclusively to the Journal "Computación y 
Sistemas", published by the Computing Research Center (CIC-IPN),
the Copyright of the aforementioned paper. I also accept that these 
rights will not be transferred to any other publication, in any other 
format, language or other existing means of developing.
I certify that the paper has not been previously disclosed or simultaneo
usly submitted to any other publication, and that it does not contain 
material whose publication would violate the Copyright or other 
proprietary rights of any person, company or institution. I certify that 
I have the permission from the institution or company where I work or 
study to publish this work.
The representative author accepts the responsibility for the publication
of this paper on behalf of each and every one of the authors. 
This transfer is subject to the following conditions:
  • The authors retain all ownership rights (such as patent rights) of this work, except for the publishing rights transferred to the CIC, through this document.
  • Authors retain the right to publish the work in whole or in part in any book they are the authors or publishers. They can also make use of this work in conferences, courses, personal web pages, and so on.
  • Authors may include working as part of his thesis, for non-profit distribution only.