Important Question of Data mining

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Unit 1.

1. Define data mining ? Explain application of data mining.
2. Explain KDD : with Diagram.
3. Explain data mining system architecture.

Unit 2.

1. Explain data mining functionalities.
2. Explain OLAP operation:
• Roll up (drill-up)
• Roll down (drill-up)
• SLICE
• DICE
• Pivot
3. Write about data warehouse schemas :
• Star Schema : characteristic, advantage, disadvantage
• Snowflake Schema : Characteristic, advantage, disadvantage
• Galaxy Schema : Characteristic, advantage, disadvantage
4. Define data warehouse architecture.
5. Difference between Data base and Data warehouse.
6. Difference between Star schema and Snowflake schema.

Unit 3.

1. Explain Data preprocessing and why it is important.
• Data Cleaning:
• Data Integration:
• Data Transformation:
• Data Reduction:
2. What is discretization ? Explain concept of hierarchy generation.

Unit 4.

1. Define clustering ? Explain K-means algorithm with example.
2. Explain K-medoids algorithm with example.
3. Difference between Agglomerative Approach and Divisive Approach.

Unit 5.

1. Difference between Classification and Predication.
2. Explain Naïve Bayes Algorithm ? How Naïve Bayes Algorithm works ?
3. Explain concept of linear regression  and non-linear regression.

Unit 6.

1. Write about Apriori algorithm.

• Itemset Frequent Pattern

    2. Generating Association from Frequent Itemset 

• FP-Growth

    3. Difference between FP growth algorithm and Apriori algorithm.

Unit 7.

1. What is an IR model ?
2. What are the component of IR model.
3. Difference between information retrieval and data retrieval.
4. Define Image Retrieval.
5. Define Video Retrieval.