DOI QR코드

DOI QR Code

Web Log Analysis Using Support Vector Regression

  • 발행 : 2003.04.01

초록

Due to the wide expansion of the internet, people can freely get information what they want with lesser efforts. However without adequate forms or rules to follow, it is getting more and more difficult to get necessary information. Because of seemingly chaotic status of the current web environment, it is sometimes called "Dizzy web" The user should wander from page to page to get necessary information. Therefore we need to construct system which properly recommends appropriate information for general user. The representative research field for this system is called Recommendation System(RS), The collaborative recommendation system is one of the RS. It was known to perform better than the other systems. When we perform the web user modeling or other web-mining tasks, the continuous feedback data is very important and frequently used. In this paper, we propose a collaborative recommendation system which can deal with the continuous feedback data and tried to construct the web page prediction system. We use a sojourn time of a user as continuous feedback data and combine the traditional model-based algorithm framework with the Support Vector Regression technique. In our experiments, we show the accuracy of our system and the computing time of page prediction compared with Pearson's correlation algorithm.algorithm.

키워드

참고문헌

  1. Proceedings of the Workshop on Recommendation system Recommendation as classification : Using Social and Content-based Information in Recommendation Basu, C.(et al.)
  2. KDDM01 Information Scent as a Driver of Web Behavior Graphs: Results of a Protocol Analysis Method for Web Usability Card, S(et al.)
  3. SIGKDD Explorations v.1 Data mining for hypertext: A tutorial survey Chakrabarti, S. https://doi.org/10.1145/846183.846187
  4. SIGIR 2000 SWAMI: A Framework for Collaborative Filtering Algorithm Development and Evaluation Fisher, D.(et al.)
  5. Data Mining: Concepts and Techniques Han, J;Kamber, M.
  6. Ann. Stat. v.13 Projection pursuit Huber, P. https://doi.org/10.1214/aos/1176349519
  7. Journal of the ACM Authoritative Sources in a Hyperlinked Environment Jon M.
  8. Proc. 2nd Berkeley symposium on Mathematiccal Statistics and Probabilistics Nonlinear programming Kuhn, H. W.;Tucker, A. W.
  9. Proceedings of Speech and Natural Language Workshop Evaluating text caterorization Lewis, D.
  10. Modern Information Retrieval Recardo, B. Y.(et. al.)
  11. Proceedings of ACM 1994 Conference on Computer Supported Cooperative Work GroupLens : An Open Architecture for collaborative filtering of Netnews Resnick, P(et al.)
  12. Introduction to Modern Information Retrieval Salton;McGill
  13. Technical Report Regression Estimation with Support Vector Learning Machines Smola, A.(et al.)
  14. Proceedings of the CHI-95 Conference Recommending and Evaluating Choices in a Virtual Community of Use Steady, W.(et al.)
  15. Machine Learning v.20 Support vector networks Vapnik, V. N.(et al.)
  16. Statistical Learning Theory Vapnik, V. N.
  17. Nature지 no.400

피인용 문헌

  1. Collaborative CRM using Statistical Learning Theory and Bayesian Fuzzy Clustering vol.11, pp.1, 2004, https://doi.org/10.5351/CKSS.2004.11.1.197