Abstract
Web content mining is an important way of Internet information collection and analysis, but most of web pages are non-XML documents, how to extract useful information efficiently from massive web pages is a interesting research topic. On the basis of analyzing the features of web content mining, a XML-based web content mining method is proposed. Firstly, it defines the authority web page using the HITS algorithms, then transforms the non-XML documents into structured XML documents after the data cleaning and extracting by HTML Tidy, finally does data mining on the XML document using text clustering techniques. A science paper web site is chosen as a case study for Web content extracting. Experimental results show that the proposed method works well, it can extract web content efficiently and automatically.
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Chen, J., Chen, H., Guo, J. (2010). Study on Method of Web Content Mining for Non-XML Documents. In: Zhu, R., Zhang, Y., Liu, B., Liu, C. (eds) Information Computing and Applications. ICICA 2010. Communications in Computer and Information Science, vol 106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16339-5_31
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DOI: https://doi.org/10.1007/978-3-642-16339-5_31
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