Applying web analysis in web page filtering
Applying web analysis in web page filtering
Vertical search engines provide Web users with an alternative way to search for information on the Web by providing customized searching in particular domains. However, two issues need to be addressed when developing these search engines: how to locate relevant documents on the Web and how to filter out irrelevant documents from a set of documents collected from the Web. This paper reports the research in addressing the second issue. In this research a machine learning-based approach that combines Web content analysis and Web structure analysis is proposed.
- University of Hong Kong China (People's Republic of)
- University of Hong Kong (香港大學) China (People's Republic of)
Web page filtering, Support vector machines, Vertical search engines, Machine learning, Web analysis, Information retrieval, Web page classification, Neural networks
Web page filtering, Support vector machines, Vertical search engines, Machine learning, Web analysis, Information retrieval, Web page classification, Neural networks
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