Data Warehousing, Mining and Business Intelligence - Dec 2013
Information Technology (Semester 7)
TOTAL MARKS: 100
TOTAL TIME: 3 HOURS (1) Question 1 is compulsory.
(2) Attempt any four from the remaining questions.
(3) Assume data wherever required.
(4) Figures to the right indicate full marks.
Attempt any four :-
1 (a) Differentiate between OLAP and OLTP(5 marks)
1 (b) What is noisy data? How to handle it.(5 marks)
1 (c) Explain constraint based association rule mining.(5 marks)
1 (d) Why is tree pruning useful in decision tree induction.(5 marks)
1 (e) What is balanced score card.(5 marks)
2 (a) Explain in details HITS algorithm in web mining.(10 marks)
2 (b) What are issue regarding classification? Different between classification and prediction.(10 marks)
3 (a) Explain Data Mining Premitives.(10 marks)
3 (b) Give the architecture of Typical Data Mining System.(10 marks)
4 (a) Consider the following database with minimum support count=60%. Find all frequent item set using Appriori and also generate strong association rules if minimum confidence =50%.
Write short notes any two :-
7 (a) Test Mining Approaches(10 marks) 7 (b) Numerority reduction.(10 marks) 7 (c) Data Discretization and Summarization.(10 marks)