Data Mining and Knowledge Engineering

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Searching Web Page Using Entropy Estimation


Affiliations
1 Department of Computer Engineering, Amrutvahini College of Engg., Sangamner, Maharashtra, India
2 Department of Computer Science and Engineering, Dr. D. Y. Patil College of Engineering, Kolhapur, Maharashtra, India
     

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Explosive growth of the web has made information search and extraction harder to the web. User needs to automatically search product based web pages to locate the product description from huge data. In this paper, we propose simple technique to locate products in the retrieved web page of the e-commercial web site. For this we are taking the benefits of hierarchical structure of HTML language. First it discovers the set of product descriptions based on the measure of entropy at each node in the HTML tag tree of the retrieved web page. Afterward, a set of association rules based on heuristic features is employed for more accuracy in the product extraction.

Keywords

Entropy, Representative Value, Association Rule, Filter, Product Description.
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  • Searching Web Page Using Entropy Estimation

Abstract Views: 257  |  PDF Views: 4

Authors

Vijay R. Sonawane
Department of Computer Engineering, Amrutvahini College of Engg., Sangamner, Maharashtra, India
P. P. Halkarnikar
Department of Computer Science and Engineering, Dr. D. Y. Patil College of Engineering, Kolhapur, Maharashtra, India

Abstract


Explosive growth of the web has made information search and extraction harder to the web. User needs to automatically search product based web pages to locate the product description from huge data. In this paper, we propose simple technique to locate products in the retrieved web page of the e-commercial web site. For this we are taking the benefits of hierarchical structure of HTML language. First it discovers the set of product descriptions based on the measure of entropy at each node in the HTML tag tree of the retrieved web page. Afterward, a set of association rules based on heuristic features is employed for more accuracy in the product extraction.

Keywords


Entropy, Representative Value, Association Rule, Filter, Product Description.