ST. ANN’S COLLEGE OF ENGINEERING & TECHNOLOGY
COMPUTER SCIENCE & ENGINEERING
Subject: Data warehousing and Data Mining
Academic Year: 2012-2013
Class: IV-CSE-A &B
ASSIGNMENT-1
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Explain the Evolution of Database Technology
Explain the Architecture of a typical data mining system
What is a Data warehouse? Briefly describe the need for data warehousing?
Explain the three-tier data warehouse architecture?
Explain about Data mining Functionalities?
Explain Major issues in Data mining?
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
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Explain Data Mining Primitives?
Explain with an example data characterization and data discrimination?
Explain Data Mining Query Language?
Briefly discuss about functional components of GUI based data mining system?
Explain about Architectures of Data Mining Systems?
ASSIGNMENT-4
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What is Concept Description?
Explain implementation of attribute-oriented induction?
Explain class comparison methods and implementation?
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?
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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? Describe back propagation algorithm?
5. What are Bayesian classifiers? With an example, describe how to predict a class label
using naive Bayesian classification?
6. Explain Fuzzy Set Approaches?
ASSIGNMENT-7
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What is cluster analysis? Describe the types of data in cluster analysis?
Describe the dissimilarity measures for interval-scaled variables and binary variables?
What is a Cluster? Briefly describe the categories of clustering techniques?
What is partitioning method? Describe k-means clustering algorithm?
What is Grid based clustering? Describe any one Grid based clustering algorithm?
What is Density based clustering? Describe DBSCAN clustering algorithm?
ASSIGNMENT-8
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What is authoritative web page? Briefly describe web usage mining?
What is multimedia data? Briefly describe the similarity search in multimedia data?
What is text mining? Describe about basic measures for text retrieval?
Explain Spatial Data Cube Construction and Spatial OLAP?
What is informational data store? Briefly describe the characteristics of informational
Data?
6. Explain Trend Analysis?