  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.
