Concept Discovery through Information Extraction in Restaurant Domain
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.
Cite
@article{arxiv.1906.05039,
title = {Concept Discovery through Information Extraction in Restaurant Domain},
author = {Nadeesha Pathirana and Sandaru Seneviratne and Rangika Samarawickrama and Shane Wolff and Charith Chitraranjan and Uthayasanker Thayasivam and Tharindu Ranasinghe},
journal= {arXiv preprint arXiv:1906.05039},
year = {2019}
}