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Sit 409: Introduction To Data Mining And Knowledge Discovery Date: Question Paper

Sit 409: Introduction To Data Mining And Knowledge Discovery Date:

Course:Bachelor Of Science ( Information Systems & Technology)

Institution: Kenyatta University question papers

Exam Year:2009

KENYATTA UNIVERSITY
UNIVERSITY EXAMINATIONS 2008/2009
INSTITUTE OF OPEN LEARNING (IOL)
EXAMINATION FOR THE DEGREE OF BACHELOR OF SCIENCE
(INFORMATION TECHNOLOGY)
SIT 409: INTRODUCTION TO DATA MINING AND KNOWLEDGE
DISCOVERY
DATE: Monday, 10th August, 2009 TIME: 11.00 a.m. – 1.00 p.m.
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INSTRUCTIONS:
Question One
a) Define
i) Data mining
ii) Information
iii) Knowledge
iv) Artificial neural networks
(10 marks)
b) List the different views of data mining (4 marks)
c) Explain four Multi-Dimensional Views of Data mining (8 marks)
d) Describe any four Data Mining Complications (8 marks)
Question Two
a) Briefly discuss data Warehouses (5 marks)
Page 2 of 2
b) Discuss why data mining is important to organization (5 marks)
c) Discuss the functions of data mining software (5 marks)
d) Sketch and label an architecture model of Data Mining System (5 marks)
Question Three
a) List four Data reduction strategies (3 marks)
b) Discuss four ways of Integration of Data Mining and Data Warehousing
(12 marks)
c) Explain the concept of Decision Support Systems (4 marks)
d) Distinguish between Classification and Prediction (4 marks)
Question Four
a) Discuss three possible techniques used in data cleaning (9 marks)
b) Distinguish between Supervised and Unsupervised learning (2 marks)
c) Briefly discuss two issues regarding classification and prediction (9 marks)
Question Five
a) Define
i) Data
ii) Error Rate
iii) Coverage
(4 marks)
b) Explain two importances of Data preprocessing (6 marks)
c) Describe five properties of a well-accepted multidimensional view (10 marks)

Sit 409: Introduction To Data Mining And Knowledge Discovery Date: Question Paper

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