About...   ©1999 Osmar R. Zaïane (zaiane@cs.ualberta.ca)

Course Content Chapter 1: Introduction Slides + Text Introduction to Data Mining What kind of information are we collecting? What are data mining and knowledge discovery? What kind of data can be mined? What can be discovered? Is all that is discovered interesting and useful? How do we categorize data mining systems? What are the issues in data mining? Chapter 2: Data Warehouses Slides + Text Data Warehouses and OLAP What is a data warehouse and what is it for? What is the multidimensional data model? What is the difference between OLAP and OLTP? What is the general architecture of a data warehouse? How can we implement a data warehouse? Are there issues related to data cube technology? Can we mine data warehouses? Chapter 3: Data Preprocessing Slides + Text Data Preprocessing What is the motivation behind data preprocessing? What is data cleaning and what is it for? What is data integration and what is it for? What is data transformation and what is it for? What is data reduction and what is it for? What is data discretization? How do we generate concept hierarchies? Chapter 4: Data Mining Operations Slides + Text Data Mining Operations What is the motivation behind data preprocessing? What is data cleaning and what is it for? What is data integration and what is it for? What is data transformation and what is it for? What is data reduction and what is it for? What is data discretization? How do we generate concept hierarchies? Chapter 5: Data Summarization Slides + Text Chapter 6: Association Rules Slides + Text Association Rule Mining What is association rule mining? How do we mine single dimensional boolean associations? How do we mine multilevel associations? How do we mine multidimensional associations? Can we constrain the association mining? Chapter 7: Data Classification Slides + Text Data Classification and prediction What is classification of data and prediction? How do we classify data by decision tree induction? What are neural networks and how can they classify? What is Bayesian classification? Are there other classification techniques? How do we predict continuous values? Chapter 8: Data Clustering Slides + Text Data Clustering What is clustering analysis? What do we use clustering for? Are there different approaches to data clustering? What are the major clustering techniques? Chapter 9: Web Mining Slides + Text Web Mining What is are the incentives of web mining? What is the taxonomy of web mining? What is web content mining? What is web structure mining? What is web usage mining? What is a Virtual Web View? Is there a query and discovery language for VWV? Similarity Search Slides + Text [Home] [Announcements] [Calendar] [On-line Materials] [Activities] [Grading] [Glossary] [U-Chat Tool] [Web Links] [Student Resources] Last updated: October 18th, 1999 [About this site and list of symbols]