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A Survey on the Classification of Dark Web Using Unclassified Ontology Method


Affiliations
1 Angel College of Engineering and Technology, Tirupur, India
     

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The deep web are the web that are not a part of surface web. Due to the large volume of data deep web have grained a large attention in recent years. Traditional search engines cannot be used to retrieve content in the deep Web. Those pages do not exist until they are created dynamically as the result of a specific search. The deep web is found to be large magnitude than the surface web. Further those deep web mostly comprises of online domain specific databases, which are accessed by using web query interfaces. In order to make the extraction relevant to user it is necessary to classify the deep web database. In this paper unclassified ontology based web classification method is used for to classify the data in the deep web. This method involves completely unclassified set of data and uses Wikipedia category network for to analyze the meta-information of the deep web sources. The result of the experiment is found to more accurate and fine-grained classification when compared to the existing approaches.

Keywords

Deep Web, Ontology, Semantic Information Retrieval, Semantic Search, Wikipedia.
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  • A Survey on the Classification of Dark Web Using Unclassified Ontology Method

Abstract Views: 257  |  PDF Views: 2

Authors

M. Sreekrishna
Angel College of Engineering and Technology, Tirupur, India
B. Chitra
Angel College of Engineering and Technology, Tirupur, India
A. Naveen Kumar
Angel College of Engineering and Technology, Tirupur, India

Abstract


The deep web are the web that are not a part of surface web. Due to the large volume of data deep web have grained a large attention in recent years. Traditional search engines cannot be used to retrieve content in the deep Web. Those pages do not exist until they are created dynamically as the result of a specific search. The deep web is found to be large magnitude than the surface web. Further those deep web mostly comprises of online domain specific databases, which are accessed by using web query interfaces. In order to make the extraction relevant to user it is necessary to classify the deep web database. In this paper unclassified ontology based web classification method is used for to classify the data in the deep web. This method involves completely unclassified set of data and uses Wikipedia category network for to analyze the meta-information of the deep web sources. The result of the experiment is found to more accurate and fine-grained classification when compared to the existing approaches.

Keywords


Deep Web, Ontology, Semantic Information Retrieval, Semantic Search, Wikipedia.