Models for User Access Patterns on the Web: Semantic Content versus Access History
PROCEEDINGS
Arun Ross, Charles Owen, Aditya Vailaya, Michigan State University, United States
WebNet World Conference on the WWW and Internet, in San Antonio, Texas Publisher: Association for the Advancement of Computing in Education (AACE), Chesapeake, VA
Abstract
This work focuses on clustering a site into groups of documents that are predictive of future user accesses. Two approaches have been developed and tested. The first approach uses semantic information inherent in the documents to facilitate the clustering process. User access history is then used to reorganize the clusters iteratively so as to better indicate access patterns. This method was found to not be an effective solution to the problem. Hence, a second method based on hierarchical clustering of trail information was developed. This method is shown to be far more effective than the first method.
Citation
Ross, A., Owen, C. & Vailaya, A. (2000). Models for User Access Patterns on the Web: Semantic Content versus Access History. In Proceedings of WebNet World Conference on the WWW and Internet 2000 (pp. 464-469). San Antonio, Texas: Association for the Advancement of Computing in Education (AACE). Retrieved August 8, 2024 from https://www.learntechlib.org/primary/p/6404/.
© 2000 Association for the Advancement of Computing in Education (AACE)
References
View References & Citations Map- [Deerwester et al., 1990] Deerwester, S., Dumais, S.T., Furnas, G.W., Landauer, T.K., and Harshman, R. (1990). Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41(6):391 –407.
- [Fowler et al., 1996] Fowler, R.H., Kumar, A., and Williams, J. (1996). Visualizing and browsing www semantic content. In Proceedings of the First Annual IEEE/ACM Conference on Emerging Technologies and Applications in Communication.
- [Green, 1998] Green, S.J. (1998). Automated link generation: can we do better than term repetition? In Seventh International WorldWide Web Conference, Brisbane, Australia.
- [Hull et al., 1996] Hull, D., Pedersen, J., and Schuetze, H. (1996). Document routing as statistical classification. Of AAAI Spring Symposium on Machine Learning in Information Access, Stanford, CA. In Proceedings [Jain and Dubes, 1988] Jain, A.K. And Dubes, R.C. (1988). Algorithms for Clustering Data. Prentice Hall, Englewood Cliffs, New Jersey. [Joshi and Krishnapuram, 1998] Joshi, A. And Krishnapuram, R. (1998). Robust fuzzy clustering methods to support web mining. In Proc. ACM SIGMOD Workshop on Data Mining and Knowledge Discovery.
- [Mobasher et al., 1996] Mobasher, B., Jain, N., Han, E.-H.S., and Srivastava, J. (1996). Web mining: Pattern discovery from worldwide web transactions. Report TR-96050, Dept. Of Computer Science, University of Minnesota. [Perkowitz and Etzioni, 1997] Perkowitz, M. And Etzioni, O. (1997). Adaptive websites: Automatically learning from user access patterns. In Sixth International WWW Conference, Santa Clara, CA, USA. [Weiss et al., 1996] Weiss, R. Et al. (1996). Hypursuit: A hierarchical network search engine that exploits content-link hypertext clustering. In Hypertext’96: The Seventh ACM Conference on Hypertext, Washington D.C., USA. [Wulfekuhler and Punch, 1997] Wulfekuhler, M.R. And Punch, W. (1997). Finding salient features for personal web page categories. In 6th International WorldWide Web Conference. Page 469
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