A Study on Designing User Web-Page Traversal Patterns Methods Using Ann

Exploring Data Mining Algorithms for Social Networking Sites

Authors

  • Poonam Rani
  • Dr. M. K. Bisht

Keywords:

designing user web-page traversal patterns methods, huge data, social networking sites, data mining, algorithm, social area networks, growth rates, social implications, best fit strategies, approaches

Abstract

The availability of all types of huge data and growing size of users for social networking sites, it would seem this area is the perfect environment for extensive data mining, research, and designing new algorithm to improve data mining on various facts. While the usage rates, public availability and uploading of huge amount of data on social media provide us a new area for research, there are a number of impediments to capitalizing on data mining algorithms with best fit strategies for this area. Studying social area networks, growth rates, and social implications of social networking sites is likely to draw strong willing for design and test new approaches of data mining from social area network sites either by owners or by users.

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Published

2017-07-01

How to Cite

[1]
“A Study on Designing User Web-Page Traversal Patterns Methods Using Ann: Exploring Data Mining Algorithms for Social Networking Sites”, JASRAE, vol. 13, no. 2, pp. 561–564, Jul. 2017, Accessed: Aug. 21, 2025. [Online]. Available: https://ignited.in/index.php/jasrae/article/view/6856

How to Cite

[1]
“A Study on Designing User Web-Page Traversal Patterns Methods Using Ann: Exploring Data Mining Algorithms for Social Networking Sites”, JASRAE, vol. 13, no. 2, pp. 561–564, Jul. 2017, Accessed: Aug. 21, 2025. [Online]. Available: https://ignited.in/index.php/jasrae/article/view/6856