STUPIDSID
1 (a)
What is Data Mining? List Challenges to data mining regarding data mining
methodology and user- interaction issues.
7 M
1 (b)
Write short note on Spatial, Legacy and Multimedia Database.
7 M
2 (a)
Differentiate between Operational Database System and Data Warehouse.
7 M
2 (b)
What is Measures? List and explain types of measures.
7 M
2 (c)
Define following terms:
1. Data Mart
2. Enterprise Warehouse
3. Virtual Warehouse.
1. Data Mart
2. Enterprise Warehouse
3. Virtual Warehouse.
7 M
3 (a)
List and describe methods for handling missing values in data cleaning.
7 M
3 (b)
What is Concept Hierarchy? List and explain types of Concept Hierarchy.
7 M
3 (c)
What is Noisy data? List and describe data smoothing techniques.
7 M
3 (d)
Why naive Bayesian classification is called "naive"? Briefly outline the major ideas of naive Bayesian classification.
7 M
4 (a)
Explain with an example attribute removal and attribute generalization.
7 M
4 (b)
State how the partitioning method may improve the efficiency of association Mining.
7 M
4 (c)
Discuss why analytical data characterization is needed and how it can be performed.
7 M
4 (d)
Briefly outline the major steps of decision tree classification.
7 M
5 (a)
What is Cluster Analysis? List and explain requirements of clustering in data
Mining.
7 M
5 (b)
Explain different types of web mining with suitable example.
7 M
5 (c)
Write the steps of the k-medoids clustering algorithm with limitation.
7 M
5 (d)
Explain the information retrieval methods used in text mining.
7 M
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