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interest areas coinciding with the related book categories. This paper suggests that bloggerspsila interests can be known through extracting keywords from blog entry titles and using book classification schemes. Because there were instances in which the keywords alone did not provide adequate information, the Naver (Korean
Writing and browsing education blogs has become one of the important methods of e-learning. Learners can search the interesting resources from these education blogs. However, the traditional blog search only provides keyword-based matching, lacking automatic extraction of learner interests and further interest-related
In this paper, reclassification for the current classification through K-means would be implemented based on the feedback of Web usage mining in order to improve the accuracy of news recommendation and convergence of classification. It could extract most relative keywords and eliminate the disturbance of multi-vocal
obtain latent semantic structure of original term-document matrix solving the polysemous and synonymous keywords problem. LS-SVM is an effective method for learning the classification knowledge from massive data, especially on condition of high cost in getting labeled classical examples. We adopt a novel method of Web page
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