Semi-Automatic Terminology Ontology Learning Based on Topic Modeling [article]

Monika Rani, Amit Kumar Dhar, O. P. Vyas
<span title="2017-08-05">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Ontologies provide features like a common vocabulary, reusability, machine-readable content, and also allows for semantic search, facilitate agent interaction and ordering & structuring of knowledge for the Semantic Web (Web 3.0) application. However, the challenge in ontology engineering is automatic learning, i.e., the there is still a lack of fully automatic approach from a text corpus or dataset of various topics to form ontology using machine learning techniques. In this paper, two topic
more &raquo; ... deling algorithms are explored, namely LSI & SVD and Mr.LDA for learning topic ontology. The objective is to determine the statistical relationship between document and terms to build a topic ontology and ontology graph with minimum human intervention. Experimental analysis on building a topic ontology and semantic retrieving corresponding topic ontology for the user's query demonstrating the effectiveness of the proposed approach.
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="">arXiv:1709.01991v1</a> <a target="_blank" rel="external noopener" href="">fatcat:quvasuunqjgk3o7ku3wtlgm5ni</a> </span>
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