AU - CS2032 Data Warehousing And Data Mining - Nov / Dec 2013 Important Questions

[Srini]

Anna University , Chennai

CS2032 Data Warehousing And Data Mining

Nov / Dec 2013 Important Questions

(Common to CSE and I.T)

Seventh Semester

2008 REG

Unit 1

1. Give the Architecture of Data warehouse and explain its usage.
2. State the difference between OLTP and OLAP in detail.
3. Explain the operations performed on data warehouse with examples.
4. Write short notes on data warehouse Meta data.
5. Explain the Conceptual Modeling of Data Warehouses.

Unit 2

1. Explain major tasks in Data Preprocessing.
2. What is data cleaning? List and explain various techniques used for data cleaning?
3. How is Attribute –Oriented Induction implemented? Explain with an example
4. Why do we preprocess the data? Explain how data preprocessing techniques can improve the quality of the data.
5. List out and describe the primitives for specifying a data mining task.

Unit 3
1. Discuss the following in detail:
             a. Association Mining
             b. Support
             c. Confidence
             d. Rule measures
2. Explain how mining will be done in frequent item sets with an example.
3. Describe join and prune steps in Apriori Algorithm.
4. Discuss the approaches for mining databases multi dimensional association rule from transactional databases. Give suitable examples.

5. (i) Explain the methods to improve the Apriori’s Efficiency.  
      (ii) Construct the FP tree for given transaction DB

   

Unit 4
1. Discuss Bayesian classification with its theorem
2. Briefly outline the major steps of decision tree classification. 

3. What is prediction? Explain about various prediction techniques. 

4. Discuss the different types of clustering methods. 

5. Describe the working of PAM (Partioning Around Medoids) algorithm.

Unit 5
1. Give some examples for text based database and explain how it is implemented using datamining system.
2. Explain mining WWW process.
3. Discuss some of the application using data mining system?
4. Describe how multidimensional analysis performed in data mining system.
5. Explain the ways in which descriptive mining of complex data objects is identified with an example