DATA WAREHOUSE & DATA MINING NOTES FOR MAKAUT

Unit=1

Introduction to Data Warehousing; Data Mining: Mining frequent patterns,

association and correlations; Sequential Pattern Mining concepts, primitives,

scalable methods;

Unit=2

Classification and prediction; Cluster Analysis – Types of Data in Cluster Analysis,

Partitioning methods, Hierarchical Methods;

Transactional Patterns and other temporal based frequent patterns,

Unit=3

Mining Time series Data, Periodicity Analysis for time related sequence data, Trend analysis, Similarity search in Time-series analysis;

Unit=4

Mining Data Streams, Methodologies for stream data processing and stream data

systems, Frequent pattern mining in stream data, Sequential Pattern Mining in

Data Streams, Classification of dynamic data streams, Class Imbalance Problem;

Graph Mining; Social Network Analysis; modulation for communication, filtering, feedback control systems.

Unit=5

Web Mining, Mining the web page layout structure, mining web link structure,

mining multimedia data on the web, Automatic classification of web documents

and web usage mining; Distributed Data Mining.

Unit=6

Recent trends in Distributed Warehousing and Data Mining, Class Imbalance

Problem; Graph Mining; Social Network Analysis