CSE4412 3.0 Data Mining (Held at the BRSU in Germany, Summer 2010)
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)