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
Not offered.
Office Hour(s)
Not offered.
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
Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied information in these areas to model and solve engineering problems.
PO-2
Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose.
PO-3
Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way so as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues according to the nature of the design.)
PO-4
Ability to devise, select, and use modern techniques and tools needed for engineering practice; ability to employ information technologies effectively.
PO-5
Ability to design and conduct experiments, gather data, analyse and interpret results for investigating engineering problems.
PO-6
Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
PO-7
Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language.
PO-8
Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
PO-9
Awareness of professional and ethical responsibility.
PO-10
Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
PO-11
Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences 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
