CSE4412 3.0 Data Mining (Held at the BRSU in Germany, Summer 2009)


Tentative Outline

Course Director: TBA

 


    ¥    08-Jun Introduction: What is Data Mining: Data Mining, Data Exploration, Knowledge Acquisition
    ¥    09-Jun Data Acquisition:     Data Bases and Data Warehouses and Data Quality    Problem Analysis (which data to mine for what? -> bias & feasability)
    ¥    10-Jun An Example: Data Mining cycle; Knowledge Mining
    ¥    15-Jun Data Preparation I
    ¥    16-Jun Data Preparation II
    ¥    17-Jun Clustering I
    ¥    18-Jun Clustering II
    ¥    19-Jun Concept Learning I
    ¥    22-Jun Concept Learning II
    ¥    23-Jun Rule Extraction I
    ¥    24-Jun Rule Extraction II
    ¥    25-Jun Applications: Text Mining, Web Mining, Multimedia Mining
    ¥    26-Jun Applications: Text Mining, Web Mining, Multimedia Mining

References: DATA MINING - Concepts, Models, Methods, and Algorithms;  Mehmed Kantardzic,  IEEE/Wiley,  2003. (Must have; Please obtain in Toronto pre-departure)