Module Descriptors
KNOWLEDGE DISCOVERY AND DATA MINING
COIS61184
Key Facts
Digital, Technology, Innovation and Business
Level 6
15 credits
Contact
Leader: Euan Wilson
Email: E.D.Wilson@staffs.ac.uk
Hours of Study
Scheduled Learning and Teaching Activities: 24
Independent Study Hours: 126
Total Learning Hours: 150
Assessment
- ASSIGNMENT (3000 WORDS APPROX) weighted at 100%
Module Details
ADDITIONAL ASSESSMENT DETAILS
An Assignment length 3000 words weighted at 100%. (Learning outcomes 1 to 4)
INDICATIVE CONTENT
Knowledge discovery and data mining in context.
Data mining primitives, languages and system architecture.
Data mining methodology and algorithms.
Text mining algorithms and Information extraction systems.
Data mining and data privacy.
Social impact and ethical issues
Data mining primitives, languages and system architecture.
Data mining methodology and algorithms.
Text mining algorithms and Information extraction systems.
Data mining and data privacy.
Social impact and ethical issues
TEXTS
Data Mining : A Knowledge Discovery Approach, K. Cios, W. Pedrycz, R. Swiniarski, L. Kurgan,: 2007., Springer, ISBN: 978-0-387-33333-5
Data Mining : Concepts and Techniques Jiawei Han, Micheline Kamber, , 2006, Morgan Kaufmann, ISBN 1558609016
Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining, Glenn J. Myatt,:2006 , John Wiley, ISBN: 0-470-07471-0
Data Mining : Concepts and Techniques Jiawei Han, Micheline Kamber, , 2006, Morgan Kaufmann, ISBN 1558609016
Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining, Glenn J. Myatt,:2006 , John Wiley, ISBN: 0-470-07471-0
LEARNING OUTCOMES
1) DEMONSTRATE SYSTEMATIC UNDERSTANDING OF THE FIELD OF KNOWLEDGE DISCOVERY, DATA MINING CONCEPTS AND METHODOLOGIES, IN ORDER TO CRTICALLY IDENTIFY THE MOST SUITABLE DATA MODELLING FOR SOLVING SPECIFIC PROBLEMS IN THE CONTEXT OF KNOWLEDGE MANAGEMENT. (Knowledge and Understanding).
2) CRITICALLY INVESTIGATE AND IDENTIFY THE BUSINESS REQUIREMENTS AND DEVELOP A MODEL FOR DATA MINING APPLICATION. (Application)
3) SELECT THE MOST SUITABLE DATA MINING TECHNIQUES FOR SOLVING SPECIFIC PROBLEMS AND TO CRITICALLY EVALUATE THEIR STRENGTHS AND LIMITATIONS. (Problem Solving)
4) CRITICALLY ANALYSE THE SOCIETAL IMPACTS AND ETHICAL ISSUES ASSOCIATED WITH DATA MINING. (Analysis)
2) CRITICALLY INVESTIGATE AND IDENTIFY THE BUSINESS REQUIREMENTS AND DEVELOP A MODEL FOR DATA MINING APPLICATION. (Application)
3) SELECT THE MOST SUITABLE DATA MINING TECHNIQUES FOR SOLVING SPECIFIC PROBLEMS AND TO CRITICALLY EVALUATE THEIR STRENGTHS AND LIMITATIONS. (Problem Solving)
4) CRITICALLY ANALYSE THE SOCIETAL IMPACTS AND ETHICAL ISSUES ASSOCIATED WITH DATA MINING. (Analysis)
Module Learning Strategies
13 lecture hours and 13 tutorial hours