Winter Semester 2010/11
Winter Semester 2011/12
Clustering algorithms in Web systems and e-business PI_ITI1208
Course content:
1.Possibility of application of clustering algorithms in Web systems.
2.Recommender systems. Collaborative filtering methods.
3.Clustering methods in recommender systems.
4.Partitioning and hierarchical clustering methods.
5.Data preprocessing. Similarity measures. Evaluation of results.
6.Adaptive WWW servers.
7.Search results recommendations.
8.Contextual and contextless ranking of WWW pages
Learning outcomes:
Knowledge about new clustering techniques and collaborative filtering methods and their application in Web systems. Acquirement of ability to process and analysis WWW serwers log files.
(in Polish) Rodzaj przedmiotu
Course coordinators
Bibliography
a) basic references:
1) Z. Markov, D. T. Larose, Data mining the Web. Uncovering patterns in Web content, structure and usage. Wiley, 2007
2) D.T. Larose: Discovering Knowledge in Data, Wiley, 2004
3) Wikipedia: http://en.wikipedia.org
4) Google Research: http://research.google.com
5) G. Linden's Blog: http://glinden.blogspot.com/
b) supplementary references:
1) D.R., Greening, Data Mining on the Web, Web Techniques, 2000
2) M. Kłopotek, Intelligent search engines, Akademicka Oficyna Wydawnicza, Warszawa, 2001 (in Polish)