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Ontology Extraction from Heterogeneous Documents

Kirankumar Kataraki, M Sumana

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Abstract

Abstract: Ontology Extraction play an important role in the Semantic Web as well as in knowledge management. The emergence of Semantic Web and the related technologies promise to make the Web a meaningful experience. Conversely, success of Semantic Web and its applications depends largely on utilization and interoperability of well-formulated ontology bases in an automated heterogeneous environment. Ontology is what exists in a domain and how they relate with each other. The advantage of an ontology is that it represents real world information in a manner that is machine understandable. This leads to a variety of interesting applications for the benefit of the target user groups. An ontology defines the terms used to describe and represent an area of knowledge. Ontologies are critical for applications that need to search across or merge information from diverse communities. In this paper, we present our approach to extract relevant ontology concepts and their relationships from a knowledge base of heterogeneous text documents.

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What this paper is about

Abstract: Ontology Extraction play an important role in the Semantic Web as well as in knowledge management. The emergence of Semantic Web and the related technologies promise to make the Web a meaningful experience. Conversely, success of Semantic Web and its applications depends largely on utilization and interoperability of well-formulated ontology bases in an automated heterogeneous environment. Ontology is what exists in a domain and how they relate with each other. The advantage of an ontology is that it represents real world information in a manner that is machine understandable. This leads to a variety of interesting applications for the benefit of the target user groups. An ontology defines the terms used to describe and represent an area of knowledge. Ontologies are critical for applications that need to search across or merge information from diverse communities. In this paper, we present our approach to extract relevant ontology concepts and their relationships from a knowledge base of heterogeneous text documents.

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Available abstract

Abstract: Ontology Extraction play an important role in the Semantic Web as well as in knowledge management. The emergence of Semantic Web and the related technologies promise to make the Web a meaningful experience. Conversely, success of Semantic Web and its applications depends largely on utilization and interoperability of well-formulated ontology bases in an automated heterogeneous environment. Ontology is what exists in a domain and how they relate with each other. The advantage of an ontology is that it represents real world information in a manner that is machine understandable. This leads to a variety of interesting applications for the benefit of the target user groups. An ontology defines the terms used to describe and represent an area of knowledge. Ontologies are critical for applications that need to search across or merge information from diverse communities. In this paper, we present our approach to extract relevant ontology concepts and their relationships from a knowledge base of heterogeneous text documents.

Key concepts: Computer science, Upper ontology, Ontology, OWL-S, Ontology-based data integration, Process ontology, Open Biomedical Ontologies, Semantic Web

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