1                  Department of Computer Science and Engg.
                                                  Arulmigu Kal...
2                  Department of Computer Science and Engg.
                                                     Arulmigu ...
3                  Department of Computer Science and Engg.
                                                  Arulmigu Kal...
4                  Department of Computer Science and Engg.
                                                  Arulmigu Kal...
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ARULMIGU KALASALINGAM COLLEGE OF ENGINEERING,

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Transcript of "ARULMIGU KALASALINGAM COLLEGE OF ENGINEERING,"

  1. 1. 1 Department of Computer Science and Engg. Arulmigu Kalasalingam College of Engineering, Krishnankoil -626190 ARULMIGU KALASALINGAM COLLEGE OF ENGINEERING, ANAND NAGAR,KRISHNANKOIL – 626 190 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING COURSE PLAN Name of the staff : Dr.S.Radhakrishnan Subject with code : Data Warehousing and Data Mining (CS1634) Course : ME Semester / Branch : III / CSE 1. Prerequisite: • Required: an introductory course on database systems. • Preferred: basic concepts in probability and statistics. 2.Objectives This course will introduce concepts and techniques of data mining and data warehousing, including concept, principle, architecture, design, implementation, application of data warehousing and data mining. Some systems for data warehousing and/or data mining will also be introduced. 3. Learning Outcome and End use. By the end of this course the student should be able to: describe and utilise a range of techniques for designing data mining and data warehousing systems. • Understand the functionality of the various data mining and data warehousing components, • Appreciate the strengths and limitations of various data mining and data warehousing models, • Compare the various approaches to data mining and data warehousing implementations, 4. Reference Books : 1. Jiawei Han, Micheline Kamber, "Data Mining: Concepts and Techniques", Morgan Kaufmann Publishers, 2002. (www.cs.sfu.ca/~han/DMbook.html) 2. Alex Berson,Stephen J. Smith, “Data Warehousing, Data Mining,& OLAP”, Tata Mcgraw- Hill, 2004. 3. Usama M.Fayyad, Gregory Piatetsky - Shapiro, Padhrai Smyth And Ramasamy Uthurusamy, "Advances In Knowledge Discovery And Data Mining", The M.I.T Press, 1996. 4. Ralph Kimball, "The Data Warehouse Life Cycle Toolkit", John Wiley & Sons Inc., 1998. Our Mission: To Produce Technically Competent, Socially Committed, And Readily Employable Computer Engineers By Offering Quality Education and Research
  2. 2. 2 Department of Computer Science and Engg. Arulmigu Kalasalingam College of Engineering, Krishnankoil -626190 5. Sean Kelly, "Data Warehousing In Action", John Wiley & Sons Inc., 1997. 5. Web Resources : 1. www.autonlab.org/tutorials : Statistical Data mining Tutorials 2. www-db.standford.edu/`ullman/mining/mining.html : Data mining lecture notes 3. ocw.mit.edu/ocwweb/slon-School-of-management/15-062Data- MiningSpring2003/course home/index.htm : MIT Data mining open courseware 4. www.kdnuggets.com: Data mining resources 6. Web links of similar courses offered at other universities 1. Purdue University : Introduction to Data mining: www.cs.purdue.edu/homes/clifton/cs490d/ 2. University of New South Wales : Data warehousing and Data mining www.cse.unsw.edu.au/~cs9318/ 3. York University: Data mining www.cs.yorku.ca/course-archieve/2005-06/w/4412/ 4. IIT- Madras : Data Mining www.iitm.ernet.in/~cs672/ 5. New york University: Data warehousing/mining www.cs.nyu.edu/courses/spring03/G22.3033-015 7. Lesson Plan Topic Topic Name Reference Book No.of Cumulative No Periods No.of Periods UNIT I INTRODUCTION 1 Introduction to Data mining R3, Chapter pp 1 1 and knowledge discovery 37-39 2 Relation To Statistics, R3, Chapter pp 1 2 Databases 39-40 3 Data Mining Functionalities R1, Chapter 1.4 pp 1 3 21-26 4 Steps In Data Mining Process R1, Chapter 1.2 pp 1 4 5-9 5 Architecture Of A Typical R1, Chapter 1.2 pp 1 5 Data Mining Systems 5-9 6 Classification Of Data Mining R1, Chapter 1.6 pp 1 6 Systems 28-30 7 Overview Of Data Mining R3, Chapter pp 1 7 Techniques 44-48 UNIT II DATA PREPROCESSING AND ASSOCIATION RULES 8 Data Preprocessing R1, Chapter 3.1 pp 1 8 105-108 9 Data Cleaning R1, Chapter 3.2 pp 1 9 Our Mission: To Produce Technically Competent, Socially Committed, And Readily Employable Computer Engineers By Offering Quality Education and Research
  3. 3. 3 Department of Computer Science and Engg. Arulmigu Kalasalingam College of Engineering, Krishnankoil -626190 109-112 10 Data Integration and R1, Chapter 3.3 pp 1 10 Transformation 112-116 11 Data Reduction R1, Chapter 3.4 pp 2 12 116-130 12 Discretization and Concept R1, Chapter 3.5 pp 2 14 Hierarchies 130-140 13 Concept Description R1, Chapter 5.1 pp 1 15 179-181 14 Data Generalization And R1, Chapter 5.2 pp 2 17 Summarization Based 181-194 Characterization 15 Mining Association Rules In R1, Chapter 6 pp 3 20 Large Databases 225-269 UNIT III PREDICTIVE MODELING 16 Classification And Prediction R1, Chapter 7.1 pp 1 21 279-282 17 Issues Regarding R1, Chapter 7.2 pp 1 22 Classification And Prediction 282-284 18 Classification By Decision R1, Chapter 7.3 pp 2 24 Tree Induction 284-296 19 Bayesian Classification R1, Chapter 7.4 pp 1 25 296-302 20 Other Classification Methods R1, Chapter 7.7 pp 1 26 314-319 21 Prediction R1, Chapter 7.8 pp 1 27 319-322 22 Clusters Analysis R1, Chapter 8.1 1 28 pp 335-338 23 Types Of Data In Cluster R1, Chapter 8.2 pp 1 29 Analysis 338-346 24 Categorization Of Major R1, Chapter 8.3 pp 1 30 Clustering Methods 346-348 25 Partitioning Methods R1, Chapter 8.4 1 31 pp 348-354 26 Hierarchical Methods R1, Chapter 8.5 pp 1 32 354-363 UNIT IV DATA WAREHOUSING 27 Data Warehousing R4 Chapter 1 1 33 Components 28 Multi Dimensional Data Model R1 Chapter 2.2 pp 2 35 44-62 29 Data Warehouse Architecture R1 Chapter 2.3 pp 2 37 62 - 71 30 Data Warehouse R1 Chapter 2.4 pp 2 38 Implementation 71-85 Our Mission: To Produce Technically Competent, Socially Committed, And Readily Employable Computer Engineers By Offering Quality Education and Research
  4. 4. 4 Department of Computer Science and Engg. Arulmigu Kalasalingam College of Engineering, Krishnankoil -626190 31 Mapping The Data Warehouse R2 Part II Chap. 8 1 39 To Multiprocessor pp 151-167 Architecture 32 OLAP.-Need- R2 Part III Chap. 1 40 33 Categorization Of OLAP 13 pp 247-266 1 41 Tools. UNIT V APPLICATIONS 34 Applications of Data Mining R1 Chapter 10.1 1 42 pp 451-457 35 Social Impacts Of Data Mining R1 Chapter 10.4 1 43 pp 472-478 36 Tools Class Notes 1 44 37 An Introduction To DB Miner R1 Appendix B pp 1 45 493 - 499 38 Case Studies Class Notes 2 47 39 Mining WWW R1 Chapter 9.6 pp 1 48 435-443 40 Mining Text Database R1 Chapter 9.5 pp 1 49 428 – 435 41 Mining Spatial Databases. R1 Chapter 9.2 pp 1 50 405 - 412 8. Portions for Monthly Test I,II and III: Sl.no Test Topic No. 1 I 01 - 15 2 II 16 - 33 3 III 34 - 41 9. Related Books and Magazines/Journals Journals IEEE Transactions on Knowledge and Data Engineering Books 1. Adriaans, P. (1996). Data mining. Addison-Wesley 2. Margaret Dunham, Data Mining: Introductory and Advanced Topics, Published by Prentice Hall 3. Weiss, Sholom M.. - Predictive data mining : a practical guide / Sholom M. Weiss, Nitin Indurkhy. - San Francisco, Calif. : Morgan Kaufmann Publishers, 1998. - 1558604030 STAFF IN-CHARGE (Dr.S.Radha Krishnan) HOD /CSE Our Mission: To Produce Technically Competent, Socially Committed, And Readily Employable Computer Engineers By Offering Quality Education and Research

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