Paper of Data Warehousing and Data Mining (CSC-459)

                                         Model Question Paper
Bachelor Level/ Fourth Year/Eight Semester/Science

Data Warehousing and Data Mining (CSC-459)                              Time:   3 hours.

Candidates are required to give their answers in their own words as far as practicable. The figures in the margin indicate full marks. 
                                       Group-A

Long Answer Questions (Attempt any Two questions)                                             [2x10=20]
1. What do you mean by data warehouse? “ The Bhatbhateni Super Store“ one of the largest departmental stores in the valley. Assume your project team got the opportunity to build the warehouse system of this departmental store. Develop the process architecture of the warehouse system and explain how you manage the responsibilities to build the ware.
2. What kind of data preprocessing do we need before applying data mining algorithm to any dataset. Explain binning method to handle noisy data with example.
3.   What is association rule analysis? Write APriori Algorithm with its pruning principle. 

                                       Group- B

Short Answer  Questions( Attempt any Eight questions)                                    [8x5=40]

 4.  What is data mining? Explain the applications of data mining.                                               [5]

 5.   What is KDD? Explain the preprocessing steps of KDD with example.                                 [5]

 6.   Explain OLAP operations with example?                                                                             [5]

 7.   List the drawbacks of ID3 algorithm with over-fitting and its remedy techniques                   [5]

 8.  Write the algorithm for K-means clustering. Compare it with k-nearest neighbor algorithm.   [5]

 9.   What is text mining? Explain the text indexing techniques.                                                     [5] 
10. Describe genetic algorithm using as problem solving technique in data mining.                       [5]

      11. What do you mean by WWW mining? Explain WWW mining techniques.                           [5]

      12. What is DMQL? How do you define Star Schema using DMQL?                                      [5]

      13. What is Prediction? Explain linear regression with example                                                 [5]