SGN-5306 KNOWLEDGE MINING, Period I, 2011, 3cr.
Professori Ari Visa, ari.visa@tut.fi
Room TF309
Phone 3115 4388
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Lectures 24 h.
Time and Place: The Course will be lectured during period I. Schedule is available at the end of this page. The first meeting will take place on the Monday, 29st of August, 10:15 a.m. in the lecture room TB224.
Topics: By the increasing popularity of the Internet and large databases the need to knowledge retrieval and management is increasing. On the course the following topics will be treated: data preprocessing, decision trees, rule based reasoning, cluster analysis, incremental learning, and so on. The lecture plan is available at the end of this page. The original lecture slides are available at the address http://www.cs.sfu.ca/~han/dmbook . The aim is to introduce the main approaches in knowledge mining and to create the capability to use and to develop the presented methods.
Audience: The course is intended to students who are close to graduation in the fields of signal processing, computer science or telecommunication. The course is also suitable to post-graduate studies.
Requirements: The examination is based on the final exam and an exercise work.
M.Sc. Marja Ruotsalainen takes care of exercise work, Email marja.ruotsalainen@tut.fi . The exercise work is available at the address http://www.cs.tut.fi/~merta/KM.html .
Literature: Data Mining: Concepts and Techniques, Jiawei Han, Micheline Kamber, Morgan Kaufmann Publisher, 2000 (DMCT).
Principles of Data Mining, David, J., Hand, Heikki Mannila, Padhric Smyth, MIT Press 2000 (PDM).
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Date |
Place |
Subject |
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29.8.2010 |
TB224 |
1. Introduction Chapter 1 DMCT |
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1.9.2010 |
TB223 |
2. Data Warehousing and OLAP technology for data mining Chapter 2 DMCT |
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5.9.2010 |
TB224 |
3. Data Preprocessing Chapter 3 DMCT, Models and Patterns Chapter 6 PDM |
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|
8.9.2010 |
TB223 |
4. Data mining primitives, languages and system architectures Chapter 4 DMCT |
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12.9.2010 |
TB224 |
5. Concept description: Characterization and Comparison Chapter 5 DMCT, Descriptive Modeling Chapter 9 PDM |
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15.9.2010 |
TB223 |
6. Mining association rules in large databases Chapter 6 |
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19.9.2010 |
TB224 |
7. Classification and prediction Chapter 7 DMCT |
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26.9.2010 |
TB224 |
8. Predictive Modeling for Classification Chapter 10 PDM |
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29.9.2010 |
TB223 |
9. Clustering analysis Chapter 8 DMCT |
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3.10.2010 |
TB224 |
10. Clustering analysis + demands for the exam Chapters 11 PDM |
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6.10.2010 |
TB223 |
11. Mining complex types of data Chapter 9 DMCT |
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10.10.2010 |
TB224 |
12. Data Mining applications and trends in data mining Chapter 10 DMCT |