Line Up: A Technique for semantic Web Visualization

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-23 Number-1
Year of Publication : 2015
Authors : Himanshu Verma, Ritesh Kumar Shah
  10.14445/22312803/IJCTT-V23P105

MLA

Himanshu Verma, Ritesh Kumar Shah "Line Up: A Technique for semantic Web Visualization". International Journal of Computer Trends and Technology (IJCTT) V23(1):22-26, May 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Semantic web mining and Synaptic web entropy mining is an important and recent research area today where number of technique presented in order to mine the web crawl efficiently and to find the web page rank of various data available in the web, in the present paper which is taken by us for the further research is the hybrid approach where the entropy is calculated based on the semantic-synaptic based approach and the important role of the entropy required today to monitor the todays web fluctuation and various stages of multiple portals and web data available today , here as the authors of the paper mentioned about the scope of the entropy monitoring ,we assume it to be a great way to make it better to experience and query search for the extracted data and entropy monitoring, we have monitored a paper Line – up approach which is efficient and determined to visualized the ranking data and optimize according to the user requirement and monitored the data efficiently, here we would like to further enhance research work on analyzing and using the entropy data as input and to use them in Line up technique to visualize and to optimize according to the user requirement in the web entropy visualization. We here mentioning and further trying to make user experience better to utilize the entropy extracted from the user and visualize them efficiently as per the user requirement.

References
1. Huiping Peng Discovery of Interesting Association Rules Based on Web Usage Mining 2010 International Conference.
2. Sanjay Kumar Malik, Nupur Prakash, S.A.M. Rizvi Ontology and Web Usage Mining towards an Intelligent Web focusing web logs 2010 International Conference.
3. Hao Yan, Bo Zhang, Yibo Zhang, Fang Liu, Zhenming Lei ―Web usage mining based on WAN users’ behaviours 2010 International Conference.
4. Han J., Pei J., Yin Y. and Mao R., ―Mining frequent patterns without candidate generation: A frequent-pattern tree approach Data Mining and Knowledge Discovery, 2004.
5. Agrawal R, Srikant R., "Fast Algorithms for Mining Association Rules", VLDB. Sep 12-15 1994, Chile, 487-99, ISBN 1-55860-153-8.
6. Mohd Helmy Abd Wahab, Mohd Norzali Haji Mohd ,Mohamad Mohsin Data Pre-processing on Web Server Logs for Generalized Association Rules Mining Algorithm 2008.
7. C.P. Sumathi, r. padmaja valli,An overview of pre-processing of web log files for web usage mining 2011.
8. Renata Ivancsy, Istvan Vajk ―Frequent Pattern Mining in Web Log Data 2006.
9. Vaibhav Kant Singh, Vijay Shah, Yogendra Kumar Jain, ―Proposing an Efficient Method for Frequent Pattern Mining 2008
10. K. R. Suneetha, Dr. R. Krishnamoorthi, ―Identifying User Behaviour by Analyzing Web Server Access Log File 2009 .
11. R. Cooly, B. Mobasher and J. Srivastava, ―Web Mining : Information and Pattern Discovery on the World Wide Web , IEEE, August 1997.Pp.558 – 566.
12. Charu C. Aggarwal and Philip S. Yu, ―An Automated Sys - tem for Web Portal Personalization, Proceedings of the 28th VLDB Conference, Hong Kong, China, 2002
13. Renáta Iváncsy, István Vajk, ―Frequent Pattern Mining in Web Log Data, Acta Polytechnica Hungarica , 2006
14. B.Santhosh Kumar, K.V.Rukmani, ―Implementation of Web Usage mining Using Apriori and FP Growth Algorithm, Int. J. of Advanced networking and Applications, (2010), Pages: 400-404
15. Shui Wang, Le Wang, ―An implementation of FP growth algorithm based on high level data structure of Weka-JUNG framework, Journal of Convergence Information Technology, Number 9, 2010 .
16. Kotsiantis S, Kanellopoulos D., ―Association Rules Mining: A Recent Overview, GESTS International Transactions on Computer Science and Engineering, 2006, pp.71- 82
17. J. Han, J. Pei, and Y. Yin. ―Mining frequent patterns with out candidate generation. IEEE, Sept.1998 pp-365-378.

Keywords
Semantic, web usage mining,entropy,sementic-synaptic approach.