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Exploring Behavior of Visitors Activity at Granular Level from Web Log Data using Deep Log Analyzer


Affiliations
1 Department of Computer Application, Maulana Azad National Institute of Technology Bhopal, Madhya Pradesh, India
     

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The World Wide Web has changed the world of information that people used to look back few decades before. Website has become the significant point of communication for business, government organization and other type of organizations to increase the business horizon and providing the effective service by the government to the people. The knowledge of user or visitor behavior plays the significant role for policy makers in going ahead. The user behavior or activity can be analyzed from web log data using the web analyzing tools. This paper covers the web log data analysis to determine visitor's behavior using the deep analyzer tool.


Keywords

WWW, Web Mining, Web Usage Mining, Deep Log Analyzer, Web Log Data Sets.
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  • Exploring Behavior of Visitors Activity at Granular Level from Web Log Data using Deep Log Analyzer

Abstract Views: 287  |  PDF Views: 0

Authors

Vinod Kumar
Department of Computer Application, Maulana Azad National Institute of Technology Bhopal, Madhya Pradesh, India
Ramjeevan Singh Thakur
Department of Computer Application, Maulana Azad National Institute of Technology Bhopal, Madhya Pradesh, India

Abstract


The World Wide Web has changed the world of information that people used to look back few decades before. Website has become the significant point of communication for business, government organization and other type of organizations to increase the business horizon and providing the effective service by the government to the people. The knowledge of user or visitor behavior plays the significant role for policy makers in going ahead. The user behavior or activity can be analyzed from web log data using the web analyzing tools. This paper covers the web log data analysis to determine visitor's behavior using the deep analyzer tool.


Keywords


WWW, Web Mining, Web Usage Mining, Deep Log Analyzer, Web Log Data Sets.