Title :
Applying Web analysis in Web page filtering
Author_Institution :
Fac. of Bus. & Econ., Hong Kong Univ., China
Abstract :
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.
Keywords :
Internet; Web sites; information filters; information retrieval; learning (artificial intelligence); neural nets; online front-ends; pattern classification; support vector machines; Web content analysis; Web document searching; Web page classification; Web page filtering; Web structure analysis; information retrieval; machine learning; neural network; support vector machine; vertical search engine; Information filtering; Information filters; Information retrieval; Machine learning; Neural networks; Search engines; Support vector machine classification; Support vector machines; Text categorization; Web pages;
Conference_Titel :
Digital Libraries, 2004. Proceedings of the 2004 Joint ACM/IEEE Conference on
Print_ISBN :
1-58113-832-6
DOI :
10.1109/JCDL.2004.1336155
