Evaluating Web Content Quality via Multi-scale Features
Information Retrieval
2013-04-24 v1
Abstract
Web content quality measurement is crucial to various web content processing applications. This paper will explore multi-scale features which may affect the quality of a host, and develop automatic statistical methods to evaluate the Web content quality. The extracted properties include statistical content features, page and host level link features and TFIDF features. The experiments on ECML/PKDD 2010 Discovery Challenge data set show that the algorithm is effective and feasible for the quality tasks of multiple languages, and the multi-scale features have different identification ability and provide good complement to each other for most tasks.
Keywords
Cite
@article{arxiv.1304.6181,
title = {Evaluating Web Content Quality via Multi-scale Features},
author = {Guang-Gang Geng and Xiao-Bo Jin and Xin-Chang Zhang and De-Xian Zhang},
journal= {arXiv preprint arXiv:1304.6181},
year = {2013}
}
Comments
4 pages, 1 figures, ecml/pkdd 2010 discovery challenge