Friday, July 31, 2015

Anna University CS9264- DATA WAREHOUSING AND DATA MEANING 2015 QP

Anna University Previous Years Question Papers
Question paper code: 41225
M.E,M.TECH DEGREE EXAMINATION,APRIL/MAY-2015
Elective
Computer science and Engineering
CS 9264/ CS 964/ 10244 CSE 51- DATA WAREHOUSING AND DATA MEANING
(Common to sixth semester information technology)
(Regulation 2008/2010)
 (Common to M.E. software Engineering and M.Tech-Information technology/ M.E Networking and Internet Engineering/ M.E. software Engineering/M. Tech multimedia Technologies)
(Regulation 2009/2010)
Time- Three hour
Maximum mark-100
Answer all questions
PART A-10X2=20marks

1. What is a data warehousing?

2. Distinguish between OLTP and OLAP.

3. Define noisy data. Give an example

4. Differentiate concept description from OLAP.

5. Define SVM.

6. How do you integrate data warehousing technique with decision tree induction?

7. List out the applications of cluster analysis.

8. What is constraint based cluster analysis.

9. Write the difference between time-series database and sequence database.

10. How does latent semantic indexing reduced the size of the term “Time frequency matrix”.

Part B-5X16=80 marks
11.(a)(i) Explain a components of a data warehousing system.
(ii) Explain the mapping methodology from data ware housing to a multiprocessor
Architecture.
(or)
(b)Explain OLAP and multidimensional data analysis.

12.(a) Explain various data mining functionalities.
(or)
(b)Define association rule mining and explain the single dimensional Boolean association rule from transactional databases?

13(a) With an example, discuss Bayesian classification.
(or)
(b)Discuss basic principle of support vector machine and draw its parallel hyper-plant between two classes.

14.(a) Explain briefly about k-Means algorithm with suitable example.
(or)
(b) Write about outlier analysis in detail.

15.(a) What is spatial database? Explain the method of mining spatial databases?
(or)
(b)(i) Discuss the social impacts of data mining.
(ii) Discuss the method of mining text databases.

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