Data Warehousing and Data Mining/Eighth sem/Elective 1

Data Warehouse and Data Warehousing, Differences between Operational Database and Data Warehouse, MOLAP, OLAP Operations, Conceptual Modeling of Data Warehouse, Components of Data Warehouse

Motivation for Data Mining, Introduction to Data Mining System, Data Mining Functionalities, KDD, Data Mining Goals

Data Types and Attributes, Various Similarity Measures, Data Cleaning, Data Integration and Transformation, Data Reduction, Data Discretization and Concept Hierarchy Generation

Cube Materialization (Introduction to Full Cube, Iceberg Cube, Closed Cube, Shell Cube), General Strategies for Cube Computation, Attribute Oriented Analysis (Attribute Generalization, Attribute Relevance, Class Comparison)

Frequent Patterns, Market Basket Analysis, Frequent Itemsets, Generating Itemsets and Association Rules, Finding Frequent Itemset (Apriori Algorithm, FP Growth), Generating Association Rules from Frequent Itemset, Limitation and Improving Apriori, Association Mining to Correlation Analysis, Constraint-Based Association Mining

Definition (Classification, Prediction), Learning and Testing of Classification, Classification by Decision Tree Induction, ID3 and Gini Index as Attribute Selection Algorithm, Bayesian Classification, Laplace Smoothing, Classification by Back Propagation, Rule Based Classifier (Decision Tree to Rules, Rule Coverage and Accuracy, Efficient of Rule Simplification), Support Vector Machine, Associative Classification, Lazy Learners, Accuracy and Error Measures, Ensemble Methods, Issues in Classification

Types of Data in Cluster Analysis, Similarity and Dissimilarity between Objects, Clustering Techniques: - Partitioning Methods, Hierarchical Methods, Density-Based Methods, Grid-Based Methods, Model-Based Clustering Methods, Clustering High-Dimensional Data, Constraint-Based Cluster Analysis, Outlier Analysis

Graph Mining, Why Graph Mining, Graph Mining Algorithm (Beam Search), Mining Frequent SubGraph, Apriori Graph, Pattern Growth Graph, Graph Indexing, Social Network Analysis, Characteristics of Social Network (Densification Power Law, Shrinking Diameter, Heavy-Tailed OutDegree and In-Degree Distributions), Link Mining (Task Involved in Link Mining, Challenges Faced by Link Mining), Friends of Friends, Viral Marketing, Community Mining, Theory of Balance, Theory of Status, Conflict Between The Theory of Balance and Status), Predicting Positive and Negative Links

Spatial Data Mining, Mining Spatial Association, Multimedia Data Mining, An Introduction to Text Mining, Natural Language Processing and Information Extraction, Web Mining (Web Content Mining, Web Structure Mining, Web Usage Mining)