ST. ANN’S COLLEGE OF ENGINEERING & TECHNOLOGY
COMPUTER SCIENCE
&
ENGINEERING
Subject:
Data warehousing and Data Mining
Academic Year: 201
2

201
3 Class: IV

CSE

A &B
ASSIGNMENT

1
1.
Explain
the
Evolution of Database Technology
2.
Explain the
Architecture of a typical data mining system
3.
What is a Data warehouse? Briefly describ
e the need for data warehousing?
4.
Explain the three

tier data warehouse architecture
?
5.
Explain about Data mining
Functionalities
?
6.
Explain Major issues in Data mining
?
7.
Steps for the Design and Construction of Data Warehouses
?
ASSIGNMENT

2
1.
Comparison between OLTP and OLAP Systems
?
2.
A data warehouse can be modeled by either a star schema or a snowflake schema.
Briefly
describe the similarities and the differences of the two models, and then analyze
their advantages and disadvantages with regard to one another
?
3.
Explain Data Cubes
?
4.
Explain Concept Hierarchy Generation
?
5.
Explain Data Preprocessing
?
ASSIGNMENT

3
1.
Explain
Data Mining Primitives
?
2.
Explain with an example data characterization and data discrimination
?
3.
Explain Data Mining Query Language
?
4.
Briefly discuss about functional components of GUI based data mining system
?
5.
Explain about Architectures of Data Mining
Systems
?
ASSIGNMENT

4
1.
What is Concept Description?
2.
Explain implementation of attribute

oriented induction?
3.
Explain class comparison methods and implementation?
4.
Explain Mining Descriptive Statistical Measures in Large Databases?
ASSIGNMENT

5
1.
Explain
Market Basket Analysis?
2.
Explain the Apriori Algorithm (Finding Frequent Itemssets using Candidate Generation)
3.
What is multilevel association? How can you mine Multilevel Association Rules?
4.
Describe
Mining Multidimensional Association Rules Using Static
Discretization of
Quantitative
Attributes
?
5.
Explain Constraint based Association Mining?
ASSIGNMENT

6
1.
What is Classification?
2.
How can you compare classification methods?
3.
What is Decision tree? With an example, briefly describe the algorithm for generating
Decision
tree?
4.
What is back propagation? Desc
ribe back propagation algorithm?
5.
What are Bayesian classifiers? With an example, describe how to predict a class label
usin
g naive Bayesian classification?
6.
Explain Fuzzy Set Approaches?
ASSIGNMENT

7
1.
What is cluster analysis? Describe the types of data in cluster analysis
?
2.
Describe the dissimilarity measures for interval

scaled variables and binary variables
?
3.
What is a Cluster? Briefly describe the cate
gories of clustering techniques?
4.
Wha
t is partitioning method? Describe k

means clustering algorithm
?
5.
What is Grid based clustering? Describe any one Grid based c
lustering algorithm?
6.
What is Density based clustering? Describe DBSCAN clustering algorithm
?
ASSIGNMENT

8
1.
What is authoritative
web page? Br
iefly describe web usage mining?
2.
What is multimedia data? Briefly describe the similarity search in multimedia data
?
3.
What is text mining? Describe about basic measures for text retrieval
?
4.
Explain Spatial Data Cube Construction and Spatial OLAP
?
5.
What is informational data store? Briefly describe the characteristics of informational
Data
?
6.
Explain Trend Analysis
?
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