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Frequent Sequential Traversal Pattern Mining for Next Web Page Prediction


Affiliations
1 Research Scholar, Rabindranath Tagore University, Bhopal, India
2 Rabindranath Tagore University, Bhopal, India
 

The web mining is a broad research area emerging to solve the issues that arise due to the WWW phenomenon. The Web mining research is a converging research area from several research communities, such as Databases, Information Retrieval and Artificial Intelligence. This work overview the most important issue of Web mining, namely sequential traversal patterns mining. In this paper, calculation of Weight and Support of every page is checked to know the importance of the web page and applied the Frequent Sequential Traversal Pattern Mining with Self Organizing Map (FSTSOM) algorithm. The performance of the proposed algorithm shows that the complete set of patterns runs considerably faster as compared to WAP Tree and FS-Tree algorithms.



Keywords

Pattern Mining, Web Page Prediction.
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  • Frequent Sequential Traversal Pattern Mining for Next Web Page Prediction

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Authors

Prabhat Kumar Sahu
Research Scholar, Rabindranath Tagore University, Bhopal, India
Rajendra Gupta
Rabindranath Tagore University, Bhopal, India

Abstract


The web mining is a broad research area emerging to solve the issues that arise due to the WWW phenomenon. The Web mining research is a converging research area from several research communities, such as Databases, Information Retrieval and Artificial Intelligence. This work overview the most important issue of Web mining, namely sequential traversal patterns mining. In this paper, calculation of Weight and Support of every page is checked to know the importance of the web page and applied the Frequent Sequential Traversal Pattern Mining with Self Organizing Map (FSTSOM) algorithm. The performance of the proposed algorithm shows that the complete set of patterns runs considerably faster as compared to WAP Tree and FS-Tree algorithms.



Keywords


Pattern Mining, Web Page Prediction.

References