DISTANCE EDUCATION
M.Sc. (Software Engineering) Years Integrated) DEGREE
EXAMINATION, DECEMBER 2017.
DATA WAREHOUSING AND MINING
Time Three hours Maximum 100 marks
SECTION A — × 8 40 marks)
Answer any FIVE questions.
1. Explain the procedure of implementing data warehouse.
2. Discuss the concept of data reduction.
3. Give a note in KDD process.
4. Narrate the concept of support vector machines.
5. Write notes on grid based methods.
6. Discuss the various prediction methods.
7. Compare and contract complete link with average link
method.
8. List and explain the various applications of web mining.
SECTION B — × 15 60 marks)
Answer any FOUR questions.
9. Write notes on the following
Classification of data mining systems.
Major issues in data mining.
10. Narrate the procedure of "Data reduction" used as data
preprocessing.
Sub. Code
44
DE-3046
WSS
2
11. Discuss the various association rules followed in large
data mining.
12. Give a neat description on clustering the high
dimensional data method.
13. Elucidate the process of classification by back
propagation.
14. Write notes on the following algorithms related to
clustering
K-means
PAM
Genetic algorithm.
15. Explain the concepts of web usage mining research and
ontology based web mining research.
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