M.Sc.DEGREE EXAMINATION,
NOVEMBER 2017
Third Semester
Computer Science
DATA MINING AND WAREHOUSING
(CBCS 2016 onwards)
Time 3 Hours Maximum 75 Marks
Part A (10 x 2 20)
Answer all questions.
1. What is snowflake schema?
2. What are the two types of data marts?
3. What is data mining?
4. Define data visualization.
5. Define frequent set.
6. What is an association rule?
7. What are the two main approaches to clustering?
8. What is the use of PAM?
9. What are the different types of web mining?
10. Define Page rank.
Sub. Code
551303
RW-984
2
Wk 11
Part B x 5 25)
Answer all questions choosing either or
11. Discuss about transformation tools.
Or
Discuss about OLAP operations.
12. Discuss in detail about the current trends in data
mining.
Or
Give a brief account of data mining techniques.
13. Discuss the importance of discovering association
rules.
Or
Describe the working of Pincer-Search algorithm.
14. Discuss about neural networks and its uses.
Or
What are the different phases of BIRCH? How they
are important in clustering?
15. Describe the essential features of temporal data and
temporal inferences.
Or
How is web usage mining different from web
structure mining and web content mining? Explain
it.
RW-984
3
Wk 11
Part C x 10 30)
Answer any three questions.
16. Explain in detail about data warehousing architecture.
17. Discuss briefly about various stages of KDD.
18. Explain briefly about Apriori algorithm with example.
19. Describe the working principles of the DBSCAN
algorithm. Explain the concept of a cluster as used in
DBSCAN.
20. How do you extract structures from unstructured text
data? What features are extracted in this process?
Explain.