NDLI: Mining Web Data Based on Ontology and SWRL

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Mining Web Data Based on Ontology and SWRL

Content Provider	Semantic Scholar
Author	Vilasrao, Vhatkar Varsha Bhaskar, Pradeep C.
Copyright Year	2012
Abstract	—In our day to day work, if we could share knowledge across systems, costs would be reduced. However, because knowledge bases are typically constructed from scratch, each with their own idiosyncratic structure, sharing is difficult. Thus recent research has focused on the use of Ontologies to promote sharing. Ontology is a hierarchically structured set of terms for describing a domain that can be used as a skeletal foundation for a knowledge base. If two knowledge bases are built on a common Ontology, knowledge can be more readily shared, since they share a common underlying structure. Ontologies provides, a shared and common understanding of a domain that can be communicated between people and application systems. Ontology is defined as partial specification of conceptual vocabulary used for formulating knowledge-level theories about a domain of discourse. Ontology is applied in domains like natural disaster Ontologies have become common place as a way to represent both knowledge and data. The knowledge provided by Ontology is extremely useful in defining the structure and scope for mining Web content, identify the meaning of data without labels and algorithm learns automatically rules expressed in Semantic Web Rule Language (SWRL) and this helps find semantic data. The Ontology is recommended for formal semantics and it is look like a backbone of every semantic web applications. In this paper a technique is proposed for ontology design using semantic web rule language. The proposed technique is useful for normal search as well as semantic search according to their senses, for semantic search the system uses the WordNet dictionary. In this system, Ontology is represented as a set of concepts and their interrelationships relevant to some knowledge domain.
Starting Page	464
Ending Page	467
Page Count	4
File Format	PDF HTM / HTML
DOI	10.7763/IJIET.2012.V2.180
Alternate Webpage(s)	http://ijiet.org/papers/180-T20000.pdf
Alternate Webpage(s)	http://www.ijiet.org/papers/180-T20000.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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