Questions
Syllabus
Qns. By Syllabus

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: 2082.1, syllabus wise question

Classification and Prediction
1.
How can you use Gini index as attribute selection algorithm? Illustrate with an example. Describe the working mechanism of support vector machine. [5+5]
2.
Discuss about lazy learners and ensemble method. [5]
Cluster Analysis
1.
Explain the types of data in clustering. [5]
2.
What is outlier? How do you cluster high dimensional data? [2+3]
3.
Differentiate between agglomerative and divisive clustering approach. [5]
Data Cube Technology
1.
Differentiate between full cube and closed cube. [5]
Data Preprocessing
1.
How do you find similarities between ordinal data attributes? Explain. [5]
Graph Mining and Social Network Analysis
1.
Define viral marketing. Describe densification power law. [2+3]
2.
What type of analysis can be performed in social network? Explain. [5]
Introduction to Data Mining
1.
List some of the data mining goals. Explain the components of data warehouse. [3+7]
Mining Frequent Patterns
1.
What is the concept behind market basket analysis? How do you generate frequent item sets using Apriori algorithm? Explain. [4+6]
Mining Spatial, Multimedia, Text and Web Data
1.
Discuss about web structure, web content and web usage mining. [5]