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Rathipriya, R.
- Extraction of Web Usage Profiles Using Simulated Annealing Based Biclustering Approach
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Authors
Affiliations
1 Department of Computer Science, Periyar University, Salem, Tamil Nadu, IN
1 Department of Computer Science, Periyar University, Salem, Tamil Nadu, IN
Source
Journal of Applied Information Science, Vol 2, No 1 (2014), Pagination: 21-29Abstract
In this paper, the Simulated Annealing (SA) based biclustering approach is proposed in which SA is used as an optimization tool for biclustering of web usage data to identify the optimal user profile from the given web usage data. Extracted biclusters are consists of correlated users whose usage behaviors are similar across the subset of web pages of a web site where as these users are uncorrelated for remaining pages of a web site. These results are very useful in web personalization so that it communicates better with its users and for making customized prediction. Also useful for providing customized web service too. Experiment was conducted on the real web usage dataset called CTI dataset. Results show that proposed SA based biclustering approach can extract highly correlated user groups from the preprocessed web usage data.Keywords
Biclustering, Clickstream Data, Simulated Annealing (SA), Web Personalization, Web User Profile, Web Recommendations, Web Usage Mining.
References
- AlMurtadha, Y. M., & Sulaiman, M. N. B., Mustapha, N. & Udzir, N. I. (2010). Mining web navigation profiles for recommendation system. Information Technology Journal, 9(4), 790-796.
- Mobasher, B., Cooley, R. & Srivatsava, J. (2000). Automatic personalization based on Web usage mining. Communication of ACM, 43(8), 142-51.
- Mobasher, B., Dai, H., Luo, T., & Nakagawa, M. (2002). Discovery and evaluation of aggregate usage profiles for web personalization. Communication of ACM, 6(1), 61-82.
- Mobasher, B., Dai, H., Luo, T. & Nakagawa, M. (2002). Improving the effectiveness of collaborative filtering on anonymous Web usage data, In Proceedings of the IJCAI.
- Mobasher, B. (1999). Web Personalizer: A ServerSide Recommender System Based on Web Usage Mining. Technical Report, Telecommunications and Information Systems.
- Bryan, K., Cunningham, P., & Bolshakova, N. (2005). Bi-Clustering of Expression Data Using Simulated Annealing. In Proceedings of the 18th IEEE Symposium on Computer Based Medical Systems.
- Castellano, G., Fanelli, A. M., & Torsello, M. A. (2011). NEWER: A system for neuro-fuzzy WEb recommendation. Applied Soft Computing, 11(1), 793-806.
- Cheng, Y., & Church, G. M. (2000). Bi-clustering of Expression Data. Proceedings of the 8th International Conference on Intelligent Systems for Molecular Biology, (pp. 93-103).
- Bryan, K., Cunnigham, P., & Bolshakova, N. (2006). Application of Simulated Annealing to the Bi-clustering of Gene Expression Data. IEEE Transactions on Information Technology in Biomedicine, 10(3), 519-525.
- Kirkpatrick, S. (1983). Simulated annealing. Science, 220(4598), 671-680.
- Liu, H., & Keselj, V. (2007). Combined mining of Web server logs and web contents for classifying user navigation patterns and predicting users' future requests. Data & Knowledge Engineering, 61(2), 304-330.
- Madeira, S. C., & Oliveira, A. L. (2004). Bi-clustering Algorithms for Biological Data Analysis: A Survey. IEEE Transactions on Computational Biology and Bioinformatics, (pp. 24-45).
- Mobasher, B. (2004). Web usage mining and personalization. In M. P. Singh (Ed.), Practical Handbook of Internet Computing. CRC Press.
- Rathipriya, R., Thangavel, K., & Bagyamani, J. (2011). Evolutionary bi-clustering of click-stream data. International Journal of Computer Science Issues, 8(1), 32-38.
- Rathipriya, R., Thangavel, K., & Bagyamani, J. (2011). Binary particle swarm optimization based Bi-clustering of web usage data. International Journal of Computer Applications, 25(2), 43-49.
- Srivatsava, J., Cooley, R., Deshpande, M., & Tan, P. N. (2000). Web usage mining: Discovery and applications of usage patterns from Web data. ACM SIGKDD Exploration, Newsletter, 1(2), 12-23.
- Gunduz, S., & Ozsu, M. T. (2003). A User Interest Model for Web Page Navigation. In Proceedings of International Workshop on Data Mining for Actionable Knowledge (DMAK), (pp. 46-57).
- Symeonidis, P., Nanopoulos, A., Papadopoulos, A., & Manolopoulos, Y. (2006). Nearest-Biclusters Collaborative Filtering. Proceedings of the WebKDD.
- Tang, C., & Zhang, A. (2001). Interrelated Two-Way Clustering: An Unsupervised Approach for Gene Expression Data Analysis. Proceedings of 2nd IEEE International Symposium Bioinformatics and Bioengineering, 14, 41-48.
- Triki, E., Collette, Y., & Siarry, P. (2005). A theoretical study on the behavior of simulated annealing leading to a new cooling schedule. European Journal of Operational Research, 166(1), 77-92.
- Zhang, Y., Xu, G., & Zhou, X. (2005). A Latent Usage Approach for Clustering Web Transaction and Building User Profile, (pp. 31-42).
- Zhou, B., Hui, S. C., & Chang, K. (2004). An Intelligent Recommender System using Sequential Web Access Patterns. IEEE Conference on Cybernetics and Intelligent Systems.
- Extraction of Protein Sequence Motif Information using PSO K-Means
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Authors
R. Gowri
1,
R. Rathipriya
1
Affiliations
1 Department of Computer Science, Periyar University, Salem, Tamilnadu, IN
1 Department of Computer Science, Periyar University, Salem, Tamilnadu, IN