Manipal University 2009 B.E Computer Science and Engineering University: ; : ; Title of the : Data Warehouse and Data Mining.(2010) - Question Paper

MANIPAL INSTITUTE OF TECHNOLOGY
(Constituent Institute of Manipal University)
MANIPAL-576104


VII SEMESTER B.E. (CSE) DEGREE exam 2009-10
SUBJECT: DATA WAREHOUSE AND DATA MINING(CSE 407.1)
DATE : 1-1-2010


TIME : three HOURS MAX.MARKS : 50



Summary: It is a Data Warehouse and Data Mining ques. Paper of 2010.This will help the engineering students to prepare more efficiently on Data Mining Subject and expertise them with the subject.

Mgii-i am

Reg No.

MANIPAL INSTITUTE OF TECHNOLOGY

(Constituent Institute of Manipal University) MANIPAL-576104

VII SEMESTER B.E. (CSE) DEGREE EXAMINATION 2009-10 SUBJECT: DATA WAREHOUSE AND DATA MINING(CSE 407.1)

DATE : 1-1-2010

TIME : 3 HOURS    MAX.MARKS : 50

Note: (i) Answer ANY FIVE full questions.

1.(a) For the tables description below, design a star schema. List the number of dimensions formed out of the design.    (4 Marks)

Time Table		Sales Table		Item Table	Location Table
Time key		Time key		Item key		Location key
Day		Item key		Item name		Street
Day of the Week		Location key		Brand		City
Month		Dollars sold		Type		State
Quarter		Units sold		Supplier_Type		Country

(b)    Explain Roll-up and Slice operations with an example for each.    (4 Marks)

(c)    Explain loosely coupled and tightly coupled DBMS to a Data Mining application.

(2 Marks)

2. (a) For the transactions given below, if the frequent itemset is {TV, Fridge, Camera} and {TV, Fridge, WM}, find all the association rules, given minimum confidence = 70%.

TID	List of Items
T1	TV, Fridge, WM
T2	Fridge, DVD Player
T3	Fridge, Camera
T4	TV, Fridge, DVD Player
T5	TV, Camera
T6	Fridge, Camera
T7	TV, Camera
T8	TV, Fridge, Camera, WM
T9	TV, Fridge, Camera

3.    (a) Write the FP-Tree algorithm for Association Rule mining.    (5 Marks) (b) Explain Naive Bayesian Classification method. (5 Marks)

4.    (a) Write the basic algorithm for decision tree construction.    (4 Marks)

(b)    Explain any one Attribute selection measure for Decision Tree construction.

(2 Marks)

(c)    Write a note on Rough Sets and Genetic Algorithms.    (4 Marks)

5.    (a) State the ways in which distance can be calculated between two Interval Scaled variables.    (4 Marks)

(b)    Write a note on Nominal and Ordinal variables.    (2 Marks)

(c)    For a Data Mining application, a Partitioning Algorithm needs to be used. It is found that the test data is free of outliers. Choose a Partitioning Algorithm and explain it.

(4 Marks)

6.(a)    Define the terms Precision and Recall with respect to Text/Web Mining. (4 Marks)

(b)    Explain the mechanism used for Page Ranking.    (2 Marks)

(c)    Explain Web Usage mining.    (4 Marks)

Attachment: manipal-university-2009-b-e-computer-science-and-engineering-3374-1.pdf

Earning:   Approval pending.