Advances in Mining the Web

author: Myra Spiliopoulou, Faculty of Computer Science (FIN), University of Magdeburg
author: Osmar R. Zaïane, Department of Computing Science, University of Alberta
author: Bamshad Mobasher, College of Computing and Digital Media, DePaul University
author: Olfa Nasraoui, Computer Engineering and Computer Science Department, University of Louisville
published: Sept. 14, 2009,   recorded: June 2009,   views: 5356


Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.

 Watch videos:   (click on thumbnail to launch)

Watch Part 1
Part 1: Mining the Social Web 53:34
Watch Part 2
Part 2: Recommendations and Personalization in the Social Web 40:01
Watch Part 3
Part 3: Dealing with Evolution in the Web 05:57
Watch Part 4
Part 4: Evolution in the Web 47:23
Watch Part 5
Part 5: Mining Wweb Data Streams 46:03


The Web has changed our way of life and the Web 2.0 has changed our way of perceiving and using the Web. Data analysis is now required in a plethora of applications that aim to enrich the experience of people with the Web. We first discuss data mining for the social Web. We elaborate on social network analysis and focus on community mining, then go over to recommendation engines and personalization. We discuss the challenges that emerged through the shift from the traditional Web to Web 2.0. We then focus on two issues - the need to protect Web applications from manipulation and the need to make them adaptive towards change. We first discuss manipulations/attacks in recommender systems and present counter-measures. We then elaborate on how changes/concept drifts can be dealt with in applications that analyze clickstream data, monitor topics in news and blogs, or monitor communities and their evolution.

This tutorial is aimed at novice researchers that have general background in data mining and are interested in understanding the potential and challenges pertinent to the social Web. The participants should have a basic understanding of recommendation engines, personalization and text modeling for mining (vector space models). They will learn how basic techniques are extended and new techniques are designed for mining the Web, especially the social Web. They will also learn about issues that are still open and require further research - research that the tutorial participants may decide to perform themselves.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Reviews and comments:

Comment1 dave, October 27, 2009 at 2 a.m.:

The audio is very choppy, and the video is not exactly High Quality.

Write your own review or comment:

make sure you have javascript enabled or clear this field: