B.C.A. DEGREE EXAMINATION, NOVEMBER 2017
Sixth Semester
Computer Applications
DATA MINING AND DATA WAREHOUSING
(CBCS 2014 onwards)
Time 3 Hours Maximum 75 Marks
Part A (10 X 2 20)
Answer all the questions.
1. Define data mining.
2. Define support.
3. What is meant by supervised learning?
4. What is pruning?
5. What is the major difference between cluster analysis
and classification?
6. List any two cluster analysis software.
7. What are the categories of web mining?
8. What is a bipartite graph?
9. Define data warehouse.
10. Define OLAP.
Sub. Code
4BCA6C1
AFF-4593
2
Ws8
Part B X 5 25)
Answer all the questions.
11. Briefly describe a data mining case study in
healthcare.
Or
Describe the association rules mining task.
12. How to construct a rule from a decision tree?
Explain with an example.
Or
List five criteria for evaluating the classification
methods. Discuss them briefly.
13. Explain expectation maximization method.
Or
How to evaluate the quality of clustering methods?
Explain.
14. Write the major differences between searching
conventional text and searching the web.
Or
Discuss about the functional areas of search engine.
15. What are the major differences between OLTP, ODS
and data warehouse systems?
Or
Explain the concept of a data cube.
AFF-4593
3
Ws8
Part C X 10 30)
Answer any three questions.
16. Discuss the efficiency of Apriori algorithm.
17. Describe the Naive Bayes method.
18. Explain the K-means partitioning method with an
example.
19. Describe the typical search engine architecture.
20. Discuss the characteristics of OLAP systems.