BIT 357                                            WITH EFFECTFROM THE ACADEMIC YEAR 2012-2013

DATA WAREHOUSING AND DATA MINING

(Elective-I)

Instruction                                                                                                           4 Periods per week
Duration of University Examination                                                                   3Hours
University Examination                                                                                     75Marks
Sessional                                                                                                            25 Marks

UNIT-I
Introduction: What is Data Mining, Data Mining Functionalities, Classification of Data Mining Systems,MajorIssues in DataMining.DataPreprocessing: Needs Preprocessing, Descriptive Data Summarization, Data Cleaning, Data Integration and Transformation, Data Reduction,
DataDiscretizationand Concept Hierarchy Generation.

UNIT -II
Data Warehouse and OLAP Technology: What is Data Warehouse, A Multidimensional Data Model, Data Warehouse Architecture and Implementation, from Data Warehousing to Data Mining.
Mining Frequent Patterns, Associations Rules: Basic Concepts, Efficient and Scalable Frequent Item Set Mining Methods, MiningVariouskinds of Association Rules.

UNIT-III
Classification and Prediction: Introduction, Issues Regarding Classification and Prediction, Classification by Decision Tree Induction, Bayesian Classification,Rulebased Classification, Classification by Back Propagation, Support Vector Machines, Prediction, Accuracy and Error
Measures

UNIT -IV
Cluster Analysis: Introduction, Types of Data in Cluster Analysis,ACategorization of Major Clustering Methods, Partitioning Methods, Hierarchical Methods, Density-Based Methods, Grid Based Methods, Model Based Clustering Methods, Outlier Analysis
 

UNIT—V
Mining Object, Spatial, Multimedia, Text, and Web Data: Multidimensional Analysis and Descriptive Mining of Complex Data Objects, Spatial Data Mining, Multimedia Data Mining, Text Mining, Mining the World Wide Web.

SuggestedReading:
1) Han J &KamberM, “Data Mining: Concepts and Techniques”, Harcourt India, Elsevier India, Second Edition.
2) Pang-NingTan. MichaelSteinback,VipinKumar, “Introduction to Data Mining”, Pearson Education, 2008.

Reference:
1) Margaret H Dunham,S.Sridhar, “Data mining: Introductory and Advanced Topics”, Pearson Education, 2008.
2)Humphires,hawkins,Dy, “Data Warehousing: Architecture and Implementation”, Pearson Education, 2009.
3)Anahory, Murray, “Data Warehousing in the Real World”, PearsonEçiucation, 2008.
4)Kargupta,Joshi,etc., “Data Mining: Next Generation Challenges and Future Directions” Prentice Hall of IndiaPvtLtd, 2007.