B.C.A. (Semester (CGPA) Examination Mar/Apr-2018
INTRODUCTION TO DATA MINING WAREHOUSING
Time: 2½ Hours
Max. Marks: 70
Instructions: All questions are compulsory. Figures to the right indicate full marks.
Q.1
Choose correct alternatives:
14
Set of items whose support count is greater than or equal to minimum support are called as
Frequent Set
Border Set
Maximal Set
Support Set
The partition of overall data warehouse is
Database
Date Cube
Data Mart
OLTP
is one of the traditional query tool.
OLAP
OLTP
SQL
MySQL
The type of relationship is present in star schema.
One to One
One to Many
Many to One
Many to Many
Any subset of a frequent set is a frequent. This phenomenon is called as
Upward closure property
Downward closure property
Frequent closure property
Frequent Set property
The next step to data selection in KDD process is
Data transformation
Data Integration
Data Cleaning
Data Coding
OLAP is nothing but
Online administration and processing
Online application processing
Online aptitude processing
Online analytical processing
The second step of A Priori algorithm is Generation.
Rule
Candidate
Large Set
Itemset
technique is used gain high-quality information from text.
Database Mining
Text Mining
Web Mining
Spatial Mining
10) of the following is a descriptive model.
Sequence discovery
Prediction
Regression
Classification
Page 2 of 2
SLR-CV-15
11) The operation of OLAP is used for reducing data cube by one or more dimensions.
Drilling
Rolling
Dicing
Slicing
12) Removing duplicate records is called as data pruning.
True
False
13) Data in data warehouse are modified.
True
False
14) is used to discover useful information from the web contents.
Web content mining
Web Usage mining
Web Structure mining
None of these
Q.2
Answer the following:
Explain continuous growth of data and different types of data used in data warehouse.
07
Explain Multidimensional Association Rule Mining in detail.
07
Q.3
Answer the following:
07
What is data warehouse? Explain data mart in detail.
07
Explain data cube technology in detail.
Q.4
Attempt any
14
What is KDD? Explain KDD in detail. Explain component of Data warehouse in detail.
Explain Text mining and Spatial mining in detail.
Q.5
Attempt any
14
What is data pre-processing? Explain different stapes involved in data pre-processing in detail.
Why Apriori algorithm is used? What are problems related with Apriori algorithm? How to increase efficiency of Apriori algorithm? Find strong association from following table (Min_support=2 and min_confidence=70%)