M.Sc. DEGREE EXAMINATION, NOVEMBER 2017
Third Semester
Computer Science
DATA MINING AND DATA WAREHOUSING
(CBCS 2014 onwards)
Time 3 Hours Maximum 75 Marks
Part A (10 x 2 20)
Answer all questions.
1. What is data mining?
2. List out the steps in knowledge discovery.
3. Define datacube.
4. Expand OLAM.
5. Define Classification.
6. What do you meant by lazy learners?
7. What is cluster analysis?
8. Expand rock.
9. How is ubiquitous data mining done?
10. Give an example for time series data.
Sub. Code
4MCE3C3
AFF-4963
2
sp 5
Part B x 5 25)
Answer all questions.
11. How data mining systems are classified? Explain
Or
Elaborate the major issues in data mining.
12. Explain about extraction and transformation in
KDD process.
Or
Write short notes on typical OLAP operations.
13. Elaborate on Baye's theorem.
Or
Make a note on back propagation algorithm.
14. What are the requirements for cluster analysis.
Or
Summarize about sting grid based method.
15. Discuss briefly on text mining.
Or
Explain the trends in Data Mining.
AFF-4963
3
sp 5
Part C x 10 30)
Answer any three questions.
16. List and explain the steps in a data mining process.
17. Explain data warehouse implementation.
18. Elucidate about Apriori algorithm.
19. Describe partitioning methods with example.
20. Discuss on multimedia data mining in brief.
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