Data Mining

Below is the syllabus for Data Mining:-

Unit I: Data Mining and Data Preprocessing

Introduction: Data Mining, Functionalities, Data Mining Systems classification, Integration with Data Warehouse System, Data summarization, data cleaning, data integration and transformation, data reduction. Data Warehouse: Need for Data Warehousing, Paradigm Shift, Business Problem Definition, Operational and Information Data Stores, Data Warehouse Definition and Characteristics, Data Warehouse Architecture and Implementation, OLAP.

Unit II: Data Generalization

Data Mining Primitives, Query Language, and System Architecture, Concept Description, Data generalization, Analysis of attribute relevance, Mining descriptive statistical measures in large databases, Data deduplication methodologies.

Unit III: Mining Associations and Correlations

Mining association rules in large databases: Association rule mining, Mining single-dimensional boolean association rules from transactional databases, mining multilevel association rules from transaction databases, Relational databases, and data warehouses, correlation analysis, classification and prediction, Data redundancy detection, and elimination techniques.

Unit IV: Cluster Analysis and Mining

Introduction to cluster analysis, Mining complex type of data: Multidimensional analysis and descriptive mining of complex data objects, Spatial databases, Multimedia databases, Mining time-series, and sequence data, Mining text databases, Mining the World Wide Web, Data Chunking Techniques.

Text Books

Han, M.Kamber, Data Mining: Concepts and Techniques, Academic Press, Morgan Kaufman Publishers, 2015.
Pieter Adrians, DolfZantinge, Data Mining, Addison Wesley
S.R. Prabhu, Data Warehousing: Concepts, Techniques, Products and Applications, Prentice Hall of India, 2014.

Reference Books

Berry and Lin off, Mastering Data Mining: The Art and Science of Customer Relationship Management, John Wiley and Sons,
Seidman, Data Mining with Microsoft SQL Server, Prentice Hall of India,2016.

Below is the link to download Data Mining notes.