Questions
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Semester

Subject

Year

Bachelors Level/Fourth Year/Eighth Semester/Science bit/eighth semester/data warehousing and data mining/syllabus wise questions

Bachelors In Information Technology

Institute of Science and Technology, TU

Data Warehousing and Data Mining (BIT454)

Year Asked: 2081, syllabus wise question

Classification and Prediction
1.
What do you understand by classification by back propagation? How is it different from Bayesian classification? Explain. [10]
Cluster Analysis
1.
List different clustering approaches. Write the algorithm of K-means algorithm. What are its limitations? [10]
Data Cube Technology
1.
Define full cube. Discuss the working mechanism of beam search. [5]
2.
Explain any two conceptual modeling techniques of data warehousing. [5]
Data Preprocessing
1.
Why is data preprocessing required? Explain any two data preprocessing methods. [5]
Graph Mining and Social Network Analysis
1.
How do you carry out social network analysis? List two of its uses. [5]
Introduction to Data Warehousing
1.
Differentiate between data warehouse and operational database. [5]
2.
What are the data mining functionalities? Explain. [5]
Mining Frequent Patterns
1.
Generate the frequent itemset from the following data using the Apriori algorithm and find the strong association rules. Minimum Support = 60%, Minimum Confidence = 75%.

$\begin{array}{|c|c|}\hline \text{TID} & \text{Items} \\ \hline 1 & \{A, C, D\} \\ 2 & \{B, C, D\} \\ 3 & \{A, B, C, D\} \\ 4 & \{B, D\} \\ 5 & \{A, B, C, D\} \\ \hline \end{array}$
[10]
Mining Spatial, Multimedia, Text and Web Data
1.
What do you mean by text mining? Explain with an example. [5]
2.
Illustrate the use of outlier analysis with an example. [5]
3.
Write short notes on: (a) OLAP (b) Laplace Smoothing [5]