The aim of this course is to introduce students the fundamentals of web mining such as web structure, web usage and content mining.
Prerequisite(s)
-
Corequisite(s)
-
Special Requisite(s)
-
Instructor(s)
Assis. Professor İsmail KOÇ
Course Assistant(s)
-
Schedule
The course is not opened for this semester.
Office Hour(s)
The course is not opened for this semester.
Teaching Methods and Techniques
-Lecture, Application.
Principle Sources
- Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications), Springer; 2nd ed. 2011 edition (July 1, 2011)
- Mining the Web: Discovering Knowledge from Hypertext Data,Morgan Kaufmann; 1 edition (October 23, 2002)
Other Sources
- Matthew A. Russell, "Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites", O'Reilly Media, ISBN: 978-1449388348, 2011.
Course Schedules
Week
Contents
Learning Methods
1. Week
Introduction to course, syllabus and learning outcomes.
Oral and written presentation.
2. Week
Web graphs.
Oral and written presentation.
3. Week
Link Analysis I
Oral and written presentation.
4. Week
Link Analysis II
Oral and written presentation.
5. Week
Web crawling
Oral and written presentation.
6. Week
Information Retrieval on the Web: Web search engines.
Oral and written presentation.
7. Week
Midterm.
Midterm.
8. Week
Information Retrieval on the Web: Query and Retrieval
Oral and written presentation.
9. Week
Web Usage Mining
Oral and written presentation.
10. Week
Collaborative Filtering I
Oral and written presentation.
11. Week
Collaborative Filtering II
Oral and written presentation.
12. Week
Latent Factor Models
Oral and written presentation.
13. Week
Hybrid Models
Oral and written presentation.
14. Week
Project Presentations
Oral and written presentation.
15. Week
16. Week
17. Week
Assessments
Evaluation tools
Quantity
Weight(%)
Midterm(s)
1
40
Homework / Term Projects / Presentations
1
20
Final Exam
1
40
Program Outcomes
PO-1
Ability to apply theoretical and practical knowledge gained by Mathematics, Science and their engineering fields and ability to use their knowledge in solving complex engineering problems.
PO-2
Ability of determining, defining, formulating and solving complex engineering problems; for that purpose develop the ability of selecting and implementing suitable models and methods of analysis.
PO-3
Ability of designing a complex system, process, device or product under real world constraints and conditions serving certain needs; for this purpose ability of applying modern design techniques
PO-4
Ability of selecting and using the modern techniques and devices which are necessary for analyzing and solving complex problems in engineering implementations; ability of efficient usage of information technologies.
PO-5
Ability of designing experiments, conducting tests, collecting data and analyzing and interpreting the solutions to investigate of complex engineering problems or discipline-specific research topics.
PO-6
Ability of working efficiently in intra-disciplinary and multi-disciplinary teams; individual working ability and habits.
PO-7
Ability of verbal and written communication skills; and at least one foreign language skills, ability to write effective reports and understand written reports, ability to prepare design and production reports, ability to make impressive presentation, ability to give and receive clear and understandable instructions
PO-8
Awareness of importance of lifelong learning; ability to access data, to follow up the recent innovation in science and technology for continuous self-improvement.
PO-9
Conformity to ethical principles; knowledge about occupational and ethical responsibility, and standards used in engineering applications.
PO-10
Knowledge about work life implementations such as project management, risk management and change management; awareness about entrepreneurship and innovativeness; knowledge about sustainable development.
PO-11
Knowledge about effects of engineering applications on health, environment and security in global and social dimensions, and on the problems of the modern age in engineering; awareness about legal outcomes of engineering solutions.
Learning Outcomes
LO-1
Students identify and differentiate among application areas for web content mining, web structure mining and web usage mining.
LO-2
Students explain in detail the architecture and main algorithms commonly used by web mining applications.
LO-3
Students explain how web search engines crawl, index, and rank web content, and assess how the web is structured
LO-4
Students apply fundamental web data mining concepts and techniques
