Data Warehousing and Data Mining
This course introduces advanced aspects of data warehousing and data mining, encompassing the principles, research results and commercial application of the current technologies.
Tribhuvan University
Institute of Science and Technology
2082
Bachelor Level / seventh-semester / Science
Computer Science and Information Technology( CSC410 )
Data Warehousing and Data Mining
Full Marks: 60 + 20 + 20
Pass Marks: 24 + 8 + 8
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.
Section A
Attempt any TWO question
Define strong association rule. What are the limitations of Apriori algorithm? Create a FP tree from the following data set.
| TID | List of Items |
|---|---|
| T1 | {A, B, C} |
| T2 | {B, C, D} |
| T3 | {C, D} |
| T4 | {B, D} |
| T5 | {A, C} |
| T6 | {A, C, D} |
What is the role of Laplace smoothing? Create a decision tree from the following data set using ID3 as attribute selection approach.
| Object | A1 | A2 | Class |
|---|---|---|---|
| 1 | T | T | C1 |
| 2 | T | T | C1 |
| 3 | T | F | C2 |
| 4 | F | F | C1 |
| 5 | F | T | C2 |
| 6 | F | T | C2 |
Consider the data set (6,3), (7,2), (4,8), (2,2), (0,2), (9,0). Taking k=3, show the result after first iteration using k-means algorithm. For choosing initial centroid, use k-means++ by taking (6,3) as initial cluster center.
Section B
Attempt any EIGHT question
Explain about data mining primitives.
Define support vector. Write the algorithm for back propagation for classification.
What is data mart? Why do we need multidimensional data model?
Describe the different types of data object and attribute types.
What is data cube? List the different variations of cube materializations.
What is the concept behind beam search? Discuss about theory of balance and status.
Explain about web content, web usage and web structure mining.
Given the following distance matrix, find the core points and outliers using DBSCAN. Take Eps = 2.5 and MinPts = 3.
| Data Points | A | B | C | D | E | F | G | H |
| A | 0 | 1.41 | 2.83 | 4.24 | 5.66 | 5.83 | 6.40 | 5.83 |
| B | 0 | 1.41 | 2.82 | 4.24 | 4.47 | 5.00 | 4.47 | |
| C | 0 | 1.41 | 2.82 | 3.16 | 3.60 | 3.16 | ||
| D | 0 | 1.41 | 2.00 | 2.24 | 2.00 | |||
| E | 0 | 1.41 | 1.00 | 1.41 | ||||
| F | 0 | 1.00 | 2.82 | |||||
| G | 0 | 2.24 | ||||||
| H | 0 |
List the components of data warehouse. Discuss about the trust propagation on social network.