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In this article, a new, efficient, feature-based semantic dissimilarity measure is proposed where the prime novelty lies in the dynamic selection of the semantic neighourhood (features) of the concepts. The neighbourhood is dynamically selected in accordance with the local density of the concept and the density of the ontology determined by the proposed density coefficient. Further, the proposed measure also scales down the dissimilarity value in accordance with the depth of the concept pair, using the novel Depth Coefficient.<\/p>","DOI":"10.4018\/ijiit.2019070102","type":"journal-article","created":{"date-parts":[[2019,5,28]],"date-time":"2019-05-28T17:10:32Z","timestamp":1559063432000},"page":"24-41","source":"Crossref","is-referenced-by-count":3,"title":["A New Dynamic Neighbourhood-Based Semantic Dissimilarity Measure for Ontology"],"prefix":"10.4018","volume":"15","author":[{"given":"Sathiya","family":"Balasubramanian","sequence":"first","affiliation":[{"name":"College of Engineering, Guindy, Anna University, Chennai, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"family":"Geetha T. 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