SHIVAJI UNIVERISTY, KOLHAPUR-416 004. MAHARASHTRA
PHONE : EPABX-2609000 GRAM : UNISHIVAJI
FAX 0091-0231-2691533 & 0091-0231-2692333 –BOS- 2609094
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Accredited By NAAC
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M.Tech Sem –I
Elective I and Elective II (any two of the following)
Elective-I
1)
Computer Vision and Image Processing.
1) Computer Vision and Image Processing
2)
Artificial Neural Network
2) Artificial Neural Network
3)
Real time Operting systems
3) Real time O.S.
4)
Data Mining
Elective –II
5)
Human and computer interaction
1) Multimedia communication
6)
Computer Modeling and Simulation
2) Embedded system
3) Data Mining
4) Geographical Information system
M.Tech Sem –II Elective- III
ElectiveIIIandElectiveIV(any two of the following)
1) Web Technology
1) Digital security
2) Computer Tecnology
2) Quantum Computing
3) Quantum Technology Computing
3) Grid Computing
4) Bio-informatics
4) Bio-Informatics
Elective –IV
5) Network Protocols
1) Advance Software Engineering
6) Mobile Computing
2) Computer Modeling and Simulation
3) Natural Language Processing
4) Grid Computing
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Mtech104 (2) –DATA MINING syllabus
1. Data warehousing and introduction to data mining.
Basic elements of data warehousing, data warehousing and OLAP
2. Data model development for data warehousing: business model, selection
of the data of interest, creation and maintaining keys, modeling
transaction, data warehousing optimization.
3. Data warehousing methodologies, type and comparisons.
4. Data mining techniques, data mining algorithms, classification,
association, associationrule mining, information extraction using neural
networks.
5. Knowledge discovery, KDD process, KDD environment.
6. Visualization data generalization and summarization based
characterization, analytical characterization, analysis of attribute
relevance, mining class comparisons, discriminating between classes,
mining descriptive statistical measures in large databases.
7. Data mining primitives, languages and system architectures, data mining
primitives, query language, desining GUI based on a data mining query
language, architecture of data mining systems.
8. Advanced topics: spatial mining, temporal mining.
9. Web mining: Web content mining, web structure mining, and web usage
mining.
10. Application and trends in data mining: Applications, systems product
and research prototypes, multimedia data mining, indexing of
multimedia material, compression, space modeling.
Text books
1
Paulraj Ponniah,”Web warehousing fundamentals”,-John Wiley
2
M.H.Dunham,”Data mining introductory and advanced topics “-Pearson
education
3
Han camber “Data mining concepts and techniques-Morgun Kaufmann
4
Imhoff Galemmo Geiger “mastering data warehouse design”-Wiley
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