Questions
Syllabus
Qns. By Syllabus

Semester

Subject

Year

Bachelors Level/Fourth Year/Seventh Semester/Science csit/seventh semester/data warehousing and data mining/syllabus wise questions

B.Sc Computer Science and Information Technology

Institute of Science and Technology, TU

Data Warehousing and Data Mining (CSC420)

Year Asked: 2076, syllabus wise question

Classification and Prediction
1.
How classification plays significance role in data mining? Explain. [5]
Data Cube Technology
1.
Explain the optimization techniques in data cube computation. [5]
Graph Mining and Social Network Analysis
1.
Discuss the types of web mining. Explain why K-means is sensitive to outlier and how does K-Medoid minimize this issue. [10]
Introduction to Data Mining
1.
Do pattern and information refer to same aspect? Justify. Differentiate between data warehouse and operational database. [10]
2.
Are the information given by data mining is always useful? What are the issues in data warehousing and data mining? [5]
3.
Give a syntax and example of data mining query language. [5]
4.
Differentiate between KDD and data mining. [5]
5.
Write short notes on (Any Two): a. Evolution analysis b. Decision trees c. Text mining d.Classification using Regression [5]
Introduction to Data Warehousing
1.
Explain the four characteristics of data warehouse. [5]
2.
How multidimensional data model helps in retrieving information? Explain with suitable example. [5]
3.
Compare the OLAP servers, ROLAP, MOLAP and HOLAP. [5]
4.
What does data warehouse tuning mean? Describe the parameters. [5]
Mining Frequent Patterns
1.
List the problems of Apriori algorithm with its possible solutions. Consider the following transaction dataset. What association rules can be found in this set, if the minimum support is 3 and the minimum confidence is 80%.

$\begin{array}{c|c} \text{Transaction_ID} & \text{Item_List} \\ \hline \text{T1} & \{K, A, D, B\} \\ \text{T2} & \{D, A, C, E, B\} \\ \text{T3} & \{C, A, B, E\} \\ \text{T4} & \{B, A, D\} \\ \end{array}$
[10]