JNTU B.Tech II Semester Examinations,
Data Warehousing And Data Mining
Time: 3 hours Max Marks: 80
Answer any FIVE Questions
All Questions carry equal marks
1. (a) Explain the major issues in data mining.
(b) Explain the three-tier datawarehousing architecture. [8+8]
2. Discuss the role of data compression and numerosity reduction in data reduction process. 
3. Write the syntax for the following data mining primitives:
(a) The kind of knowledge to be mined.
(b) Measures of pattern interestingness. 
4. (a) What are the differences between concept description in large data bases and OLAP?
(b) Explain about the graph displays of basic statistical class description. [8+8]
5. Explain the Apriori algorithm with example. 
6. (a) Describe the data classification process with a neat diagram.
(b) How does the Naive Bayesian classification works? Explain.
(c) Explain classifier accuracy. [5+5+6]
7. (a) Given two objects represented by the tuples (22,1,42,10) and (20,0,36,8):
i. Compute the Euclidean distance between the two objects.
ii. Compute the Manhanttan distance between the two objects.
iii. Compute the Minkowski distance between the two objects, using q=3.
(b) Explain about Statistical-based outlier detection and Deviation-based outlier detection. [3+3+4+3+3]
8. Explain the following:
(a) Constriction and mining of object cubes
(b) Mining associations in multimedia data
(c) Periodicity analysis
(d) Latent semantic indexing. [4+4+4+4]