DISTANCE EDUCATION
M.Sc. (Software Engineering) Year Integrated) DEGREE
EXAMINATION, MAY 2018.
DATA WARE HOUSING AND MINING
Time Three hours Maximum 100 marks
PART A — × 8 40 marks)
Answer any FIVE questions.
1. Give a note on data warehousing.
2. Discuss the concept of data cleaning.
3. Write about multidimensional and multirelational OLAP.
4. Write notes on K-nearest neighbour classifiers.
5. Summarize the grid based methods used for clustering.
6. Elucidate the frequent pattern based clustering methods.
7. Compare K-means partitioning method with K-medoids
partitioning method.
8. Discuss the concept of web content mining.
PART B — × 15 60 marks)
Answer any FOUR questions.
9. Give a neat description on data mining functionalities.
10. Describe the concept of data warehouse architecture.
Sub. Code
44
DE-4158
11. Elucidate the process of classification by decision tree
induction.
12. Explain in detail about the Bayesian classification
methodology.
13. Give a detailed description on outlier analysis method.
14. Explain in detail about any three partitional algorithms.
15. Discuss on taxonomy of web knowledge mining and
ontology based web mining.