Open AccessAn Ontology Approach to Data Integration using Mapping Method
Author(s) -
Dr.A.Mekala
Publication year - 2020
Publication title -
international journal of modern trends in science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-3778
DOI - 10.46501/ijmtst061206
Subject(s) - computer science , ontology , information retrieval , categorization , ontology based data integration , task (project management) , data integration , semantic integration , focus (optics) , data mining , artificial intelligence , semantic web , semantic computing , philosophy , physics , management , epistemology , optics , economics
Text mining is a technique to discover meaningful patterns from the available text documents. The patternsighting from the text and document association of document is a well-known problem in data mining.Analysis of text content and categorization of the documents is a composite task of data mining. Some of themare supervised and some of them unsupervised manner of document compilation. The term “FederatedDatabases” refers to the in sequence integration of distributed, autonomous and heterogeneous databases.Nevertheless, a federation can also include information systems, not only databases. At integrating data, morethan a few issues must be addressed. Here, we focus on the trouble of heterogeneity, more specifically onsemantic heterogeneity – that is, problems correlated to semantically equivalent concepts or semanticallyrelated/unrelated concepts. In categorize to address this problem; we apply the idea of ontologies as a tool fordata integration. In this paper, we make clear this concept and we briefly explain a technique for constructingontology by using a hybrid ontology approach.