Data Warehousing and Data Mining 2075

        Group - A

Attempt any two Questions.        (10 x 2 = 20)

1. List some issues of multimedia mining. Describe how back propagation is used in classification.

2. Describe how bitmap and join indexing are used to represent OLAP data. Explain the different components of data warehouse.

3. Give any two types of association rules with example. Trace the results of using the Apriori algorithm on the grocery store example with support threshold 2 and confidence threshold 60 %. Show the candidate and frequent itemsets for each database scan. Enumerate all the final frequent itemsets. Also indicate the association rules that are generated.

        Group - B

Attempt any eight Questions.        (8 x 5 = 40)

4. What is the purpose of cluster analysis in data mining? Explain.

5. How does KDD differ with data mining? Describe the stages of data mining.

6. Explain OLAP operations with examples.

7. Explain the primitives of data mining query language.

8. How different schema are used to model data warehouse? Explain.

9. Describe the significances of pre-computation of data cube.