Genetic Algorithm based Feature Selection for Ontology based Information Retrieval of Semi Structure Data
N. Vanjulavalli1, Dr. A. Kovalan 2
1. Research Scholar,Department of Computer Science and Applications,PMU, Vallam, Thanjavur
2. Assistant Professor (S.S), Department of Computer Science and Applications,PMU, Vallam, Thanjavur.
Abstract: The increasing volume of web pages in World Wide Web in the form of free-text makes information retrieval difficult. The retrieval is more challenging due to the ambiguous nature of the unstructured information found in these pages. Ontologies help to overcome the disambiguate nature of the natural language by the use of standard terms that relate to specific concepts. Thus, the knowledge of ontology is used to match object and queries based on semantics improving information retrieval. In this paper, the features from the web pages are extracted based on ontology and semantics of the XML tags. Genetic Algorithm is applied for selecting optimal subset of features based on correlation. Experimental results for the proposed feature extraction method demonstrate the effectiveness of the optimization of the feature selection.
[N. Vanjulavalli, A. Kovalan. Genetic Algorithm based Feature Selection for Ontology based Information Retrieval of Semi Structure Data. Life Sci J 2013;10(7s):516-521]. (ISSN: 1097-8135). http://www.lifesciencesite.com. 80
Keywords: Information retrieval (IR), World Wide Web, Ontology, Feature Selection, Genetic Algorithm, Bagging.