GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
WEB MINING/5251310
Course Title: WEB MINING
Credits 3 ECTS 8
Semester 2 Compulsory/Elective Elective
COURSE INFO
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- NAME OF LECTURER(S)
  Prof. Dr. M. Ali Akcayol
 -- WEB SITE(S) OF LECTURER(S)
  http://w3.gazi.edu.tr/web/akcayol/
 -- EMAIL(S) OF LECTURER(S)
   akcayol@gazi.edu.tr
 -- LEARNING OUTCOMES OF THE COURSE UNIT
Learning data mining and eb mining
Learning association rules
Learning supervised and unsupervised learning
Learning information retrieval
Learning web search
Learning link analysis
Learning Web crawling
 -- MODE OF DELIVERY
   The mode of delivery of this course is face to face
 -- PREREQUISITES AND CO-REQUISITES
   There is no prerequisite or co-requisite for this course
 -- RECOMMENDED OPTIONAL PROGRAMME COMPONENTS
   There is no recommended optional programme component for this course
 --COURSE CONTENT
1. Week  Data mining and Web mining
2. Week  Association rules
3. Week  Ordered patterns
4. Week  Supervised learning
5. Week  Classification using supervised learning
6. Week  Unsupervised learning
7. Week  Clustering using unsupervised learning
8. Week  Midterm
9. Week  Information retrieval
10. Week  Information retrieval
11. Week  Web search
12. Week  Web search
13. Week  Link analysis
14. Week  Web crawling
15. Week  Web crawling
16. Week  
 -- RECOMMENDED OR REQUIRED READING
  Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data, Bing Liu, Springer, 2011.
 -- PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
   The mode of delivery of this course is face to face
 -- WORK PLACEMENT(S)
  -
 -- ASSESSMENT METHODS AND CRITERIA
 
Quantity
Percentage
 Mid-terms
1
35
 Assignment
6
25
 Exercises
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Contribution of In-term Studies to Overall Grade  
60
 Contribution of Final Examination to Overall Grade  
40
 -- WORKLOAD
 Efficiency  Total Week Count  Weekly Duration (in hour)  Total Workload in Semester
 Theoretical Study Hours of Course Per Week
14
3
42
 Practising Hours of Course Per Week
0
0
0
 Reading
14
2
28
 Searching in Internet and Library
14
2
28
 Designing and Applying Materials
0
0
0
 Preparing Reports
8
5
40
 Preparing Presentation
0
0
0
 Presentation
0
0
0
 Mid-Term and Studying for Mid-Term
1
20
20
 Final and Studying for Final
1
36
36
 Other
0
0
0
 TOTAL WORKLOAD: 
194
 TOTAL WORKLOAD / 25: 
7.76
 ECTS: 
8
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1Improves and deepens the field knowledge at an expert level based on undergraduate proficiency.X
2Comprehends the interactions between the computer science and other related disciplines.X
3Uses expert level theoretical and practical knowledge acquired in the computer science field.X
4Creates new knowledge by integrating the computer science knowledge and the knowledge from related disciplines.X
5Defines a problem in the computer science field.X
6Analyses the problems in the computer science field by using scientific research methods.X
7Proposes solutions to the problems in the computer science field.X
8Solves problems in the computer science field.X
9Evaluates the results within perspectives of quality processes.X
10Develops new approaches and methods by taking responsibility in complex situations in the application stages.X