A Method of Web Page Classification Based on Feature Dimension Reduction

Xun-yi REN, Dan ZHANG

Abstract


Text classification technology to quickly retrieve information pages, information filtering and data mining provides an important foundation. Due to the diversity and complexity of web page format, the problem of web page classification is more difficult to deal with than text classification. This paper on web page classification method research, through the improvement of bloom filter, after pretreatment of the text content of pages, the improved bloom filter used in filtering feature set, greatly reducing the feature dimension, then according to the characteristics of web page, the feature weight algorithm has been improved. Finally, using the naive Bayesian classifier can verify the effectiveness of the algorithm.

Keywords


Web page classification, Bloom filter, Feature weight, Naive bayes

Publication Date


2016-11-17 00:00:00


DOI
10.12783/dtcse/cmsam2016/3617

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