Clustered Hierarchical Concept Based Semantic Closeness Between Two Concepts Using WordNet
The search engine needs relatedness to measure closeness between two concepts for determining optimal results in major applications like information retrieval, information integration and of many more in natural language processing tasks i.e. text classification, word sense disambiguation, matching problems in artificial intelligence etc,. The clustered hierarchical concept network helps to overcome the fuzzy variations in different levels of granularity in measures of closeness based on weights, frequency or distances but these measures are not considered since no method takes the actual context of the user intention, user query or context domain subject fields. Clustered hierarchical concept network has three steps: Elicitation: extract the concepts of user query using concept extraction algorithm and name the output as context domain. Construction: building hierarchical clusters based on context or concept domain with related concepts as nodes and relations as edges. Matching: determine the matching concepts like Least Common General Concept (LCGC) and Least Common Specific Concept (LCSC). Clustered hierarchical concept based semantic closeness has three features i.e., context domain, concept net and common concepts. These features are used to calculate the relatedness. The primary goal of hierarchical concept network is to include the semantic of the concept by including its three features. The extraction of concepts are not only related to individual concepts, but it is also an organizational structure of the concepts that are combined in the ontology i.e. WorNet. In this paper, we propose a method for computing semantic closeness of two concepts in which the holonyms, meronyms, instances of concepts are considered synthetically. By calculating test data, the experiment results show that the method can compute concepts closeness effectively. The human judgments on a set of concept pairs led our approach to be more effective and shown one of the best performance than the measures based on concept vector.
Keywords: Search Engine, Word Sense, Relatedness, Clustered Hierarchical Concept, Elicitation, Construction, Matching, LCGC, LCSC, WordNet, Holonyms, Meronyms and Instances.
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ABOUT THE AUTHORS
Boddu Bhaskara Rao
Mr. B.Bhaskara Rao is presently working as Associate Professor in the department of Information Technology, GIT, GITAM University, Visakhapatnam, Andhra Pradesh, India. He presented several research papers in national and international conferences and seminars. He published a good number of papers in national and international journals. He guided several students for getting their M.Tech degrees in Information Technology. His current research interests are Information Retrieving, Semantics and Internet Technologies.
V. Valli Kumari
Dr. V. Valli Kumari is presently working as Professor in the Department of Computer Science and Systems Engineering, College of Engineering(A), Andhra University, Visakhapatnam, Andhra Pradesh, India.She got her Ph.D degree from Anhdra University in Computer Science and Systems Engineering in 2005 and got gold medal for best research, awarded at 75th convocation of Andhra University, January 2008. She has published several research papers and delivered invited lectures at various conferences, seminars and workshops. She guided a number of students for their Ph.D and M.Tech degrees in Computer Science and Engineering and Information Technology. Her current research interests are Agent Software, Privacy Issues in Data Mining and web Technology, Image Processing, Network Security and Cryptography, Software engineering.
Boddu Bhaskara Rao
Mr. B.Bhaskara Rao is presently working as Associate Professor in the department of Information Technology, GIT, GITAM University, Visakhapatnam, Andhra Pradesh, India. He presented several research papers in national and international conferences and seminars. He published a good number of papers in national and international journals. He guided several students for getting their M.Tech degrees in Information Technology. His current research interests are Information Retrieving, Semantics and Internet Technologies.
V. Valli Kumari
Dr. V. Valli Kumari is presently working as Professor in the Department of Computer Science and Systems Engineering, College of Engineering(A), Andhra University, Visakhapatnam, Andhra Pradesh, India.She got her Ph.D degree from Anhdra University in Computer Science and Systems Engineering in 2005 and got gold medal for best research, awarded at 75th convocation of Andhra University, January 2008. She has published several research papers and delivered invited lectures at various conferences, seminars and workshops. She guided a number of students for their Ph.D and M.Tech degrees in Computer Science and Engineering and Information Technology. Her current research interests are Agent Software, Privacy Issues in Data Mining and web Technology, Image Processing, Network Security and Cryptography, Software engineering.
