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http://dx.doi.org/10.3745/KIPSTD.2003.10D.2.277

Sparse Web Data Analysis Using MCMC Missing Value Imputation and PCA Plot-based SOM  

Jun, Sung-Hae (청주대학교 통계학과)
Oh, Kyung-Whan (서강대학교 컴퓨터학과)
Publication Information
The KIPS Transactions:PartD / v.10D, no.2, 2003 , pp. 277-282 More about this Journal
Abstract
The knowledge discovery from web has been studied in many researches. There are some difficulties using web log for training data on efficient information predictive models. In this paper, we studied on the method to eliminate sparseness from web log data and to perform web user clustering. Using missing value imputation by Bayesian inference of MCMC, the sparseness of web data is removed. And web user clustering is performed using self organizing maps based on 3-D plot by principal component. Finally, using KDD Cup data, our experimental results were shown the problem solving process and the performance evaluation.
Keywords
Hybrid MCMC Missing Value Imputation; Self Organizing Maps; Principal Component based Plot;
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