Instructor:
Mustafa
Ozdal (EA420).
TA: Selcuk Gulcan (selcuk.gulcan _at_ bilkent.)
Textbook:
A. Rajaraman
and J. D. Ullman, Mining of
Massive Datasets, Cambridge University Press, 2011. Online free version
available at: http://www.mmds.org
Schedule: Tue:
13:40 - 15:30; Thu: 15:40 - 17:30
Office Hour: Tue: 15:40 - 16:30 (EA420)
Syllabus:
syllabus.pdf
Course
Project:
The project description can be found here.
Lectures
Note: Some lecture notes provided below
contain slides from the course
textbook. Some of
these slides have been modified for the purpose of
this class. The original slides from the textbook can be accessed here.
Lecture
1:
PageRank Formulation and Algorithm (slides: ppt, pdf; reading
material: Chapter
5)
Lecture
2:
PageRank Extensions (slides: ppt,
pdf;
reading material: Chapter
5)
Lecture
3:
Shingling, Min-Hashing, and LSH (slides: ppt, pdf;
reading material: Chapter
3)
Lecture
4:
LSH Applications (slides: ppt, pdf;
reading material: Chapter
3)
Lecture
5:
MapReduce Model and Examples (slides: ppt, pdf; reading
material: Chapter
2)
Lecture
6:
MapReduce Complexity Analysis and Improved
Algorithms (slides: ppt,
pdf;
reading material: Chapter
2)
Lecture
7:
Web Advertising (slides: ppt, pdf;
reading material: Chapter
8)
Lecture
8:
Recommendation Systems: Content-Based and
Collaborative Filtering
(slides: ppt, pdf;
reading material: Chapter
9)
Lecture
9:
Recommendation Systems: Latent Factor Models
and Netflix Challenge
(slides: ppt, pdf;
reading
material: Chapter
9)