Exam Details
Subject | data ware housing and mining | |
Paper | ||
Exam / Course | m.sc. (software engineering) | |
Department | ||
Organization | Alagappa University Distance Education | |
Position | ||
Exam Date | May, 2016 | |
City, State | tamil nadu, karaikudi |
Question Paper
DISTANCE EDUCATION
M.Sc. (Software Engineering) Year Integrated) DEGREE
EXAMINATION, MAY 2016.
DATA WAREHOUSING AND MINING
Time Three hours Maximum 100 marks
SECTION A — 8 40 marks)
Answer any FIVE questions.
1. Explain any two kinds of data mining.
2. What is optimizing Data for mining?
3. Discuss fuzzy sets and logic.
4. Explain in details about pattern matching.
5. Describe the Neural network.
6. Explain the Clustering issues.
7. Illustrate any one Partitional algorithm.
8. Describe briefly on web mining applications.
Sub. Code
44
DE-3922
2
wk 3
SECTION B — 15 60 marks)
Answer any FOUR questions.
9. Discuss the classification of data mining system.
10. Illustrate the MLE.
11. Explain any two summarization models.
12. Describe the clustering approaches.
13. Explain in detail about SingleLink and MST SingleLink
algorithm for clustering.
14. Explain BEA algorithm.
Explain-GA algorithm.
15. Briefly explain about Web Knowledge Mining Taxonomy.
M.Sc. (Software Engineering) Year Integrated) DEGREE
EXAMINATION, MAY 2016.
DATA WAREHOUSING AND MINING
Time Three hours Maximum 100 marks
SECTION A — 8 40 marks)
Answer any FIVE questions.
1. Explain any two kinds of data mining.
2. What is optimizing Data for mining?
3. Discuss fuzzy sets and logic.
4. Explain in details about pattern matching.
5. Describe the Neural network.
6. Explain the Clustering issues.
7. Illustrate any one Partitional algorithm.
8. Describe briefly on web mining applications.
Sub. Code
44
DE-3922
2
wk 3
SECTION B — 15 60 marks)
Answer any FOUR questions.
9. Discuss the classification of data mining system.
10. Illustrate the MLE.
11. Explain any two summarization models.
12. Describe the clustering approaches.
13. Explain in detail about SingleLink and MST SingleLink
algorithm for clustering.
14. Explain BEA algorithm.
Explain-GA algorithm.
15. Briefly explain about Web Knowledge Mining Taxonomy.
Other Question Papers
Subjects
- c programming – lab
- c++ lab
- case tools lab
- computer graphics and multimedia
- computer networks
- cryptography and network security
- data structures lab
- data ware housing and mining
- distributed computing
- internet and java - lab
- internet and java programming
- mobile communications
- object oriented programming and c++
- open source architecture
- open source lab
- operating systems
- relational database management system
- relational database management systems –lab
- software engineering
- software project management and metrics
- software quality assurance and standards
- software testing and reuse
- unix and shell programming
- visual basic and vc++ lab
- visual programming
- web technology
- web technology — lab