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The Web continues to grow and evolve very fast, changing our daily lives. This activity represents the collaborative work of the millions of institutions and people that contribute content to the Web as well as the one billion people that use it. In this ocean of hyperlinked data there is explicit and implicit information and knowledge. Web Mining is the task of analyzing this data and extracting information and knowledge for many different purposes. The data comes in three main flavors: content (text, images, etc.), structure (hyperlinks) and usage (navigation, queries, etc.), implying different techniques such as text, graph or log mining. Each case reflects the wisdom of some group of people that can be used to make the Web better, for example, user generated tags in Web 2.0 sites. In this tutorial we will walk through the mining process and will show several applications, ranging from Web site design to search engines. The main goal is to introduce AI researchers to the myriad of challenges in Web mining, where other AI techniques, in addition to machine learning, might be applicable.
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