Abstract
Web mining is a rapid growing research area. It consists of Web usage mining, Web structure mining, and Web content mining. Web usage mining refers to the discovery of user access patterns from Web usage logs. Web structure mining tries to discover useful knowledge from the structure of hyperlinks. Web content mining aims to extract/mine useful information or knowledge from web page contents. This tutorial focuses on Web Content Mining. A web browser of a limited size has difficulty in expressing on a screen information about goods like an Internet shopping mall. Page scrolling is used to overcome such a limitation in expression. For a web page using page scrolling, it is impossible to use click-stream based analysis in analyzing interest for each area by page scrolling. In this study, a web-using mining system is presented, designed, and implemented using page scrolling to track the position of the scroll bar and movements of the window cursor regularly within a window browser for real-time transfer to a mining server and to analyze user’s interest by using information received from the analysis of the visual perception area of the web page.
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Kim, HK., Lee, R.Y. (2009). Frameworks for Web Usage Mining. In: Lee, R., Ishii, N. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. Studies in Computational Intelligence, vol 209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01203-7_10
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DOI: https://doi.org/10.1007/978-3-642-01203-7_10
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