Syllabus
Objectives |
Grading |
Policies |
Academic integrity |
Remarks
Course description and learning objectives
The course will cover machine learning techniques to mine the Web and other
information networks, social networks, and social media.
We will discuss applications to search, retrieval, classification, and recommendation.
Various models to explain the dynamics of Web processes will also be emphasized.
Topics to be covered will include:
- Web crawling
- Indexing
- Text analysis and classification
- Link analysis
- Ranking algorithms
- Web search and retrieval
- Clustering/community algorithms
- Topical locality
- Web growth models
- Web traffic models
- Social tagging
- Social networks and social media
- Information diffusion
Students will work on a semester-long group project on one of the topics covered in class.
Students will:
- learn to critically read and connect a significant amount of scientific literature;
- practice effective technical presentation skills;
- become familiar with classic and recent developments in Web search and data mining;
- acquire statistical techniques to analyze complex information and social networks;
- study several models to interpret emergent features such as the structure and evolution of the Web graph, its traffic patterns, and the spread of information; and
- apply technical and analytic skills to develop a significant group research project, with the opportunity to submit the results for publication
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Class organization and tentative grading
| Component |
Weight |
Notes |
| Presentation of readings and leading of discussion |
25% |
Each student will be responsible to present some papers and lead class discussion on those papers. Grading is based on student's capability to synthesize critical contributions and foster a lively discussion capable of bringing key insights and connections into light. Hint: lots of slides with lots of text bullets typically do not work well. You can find lots of great examples of effective short presentations. |
| Participation in class and online discussions |
25% |
Each student is expected to read all papers ahead of class discussion and participate actively in the discussion. Participation grade is based on demonstrated familiarity with assigned readings and capability to make critical observations and to contribute constructively to the discussion. |
| Project |
50% |
Students will form groups and identify project topics at the beginning of the semester. They will develop a timeline, submit a proposal, and receive feedback from instructor and/or AIs. They will submit a progress report due around week 10, and a final project report (in conference poster proceedings format) due at the end of the semester. They will also maintain a wiki as an open lab notebook. Grading will be based on quality of reports and wiki, an in-class project presentation, and an interview to demonstrate the project. |
If a student submits to a relevant conference a paper documenting a project from this course, and the paper gets accepted for publication within a semester after the end of this course, the instructor will change the course final grade to A or A+ (at his discretion). Relevant conferences include WWW, WSDM, SIGIR, KDD, CIKM, ICWSM, SocialCom, Web Science, WI, and others (to be approved by instructor).
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Class policy
- The main communication medium outside of class is the discussion group.
Students are expected to post their questions,
answer other students' questions, post pointers to relevant technology
news (do NOT copy and paste news articles!), and check the list daily
for announcements. Postings must be signed in order to get
participation credit.
- Students are responsible for assigned readings PRIOR to class
discussions.
- If your cell phone rings during class, you owe $1 to the shame fund.
Proceeds will be donated to a charity at the end of the semester.
- If you miss class, it is your responsibility to find out about any
announcements or assignments you may have missed.
- The instructor reserves the right to take into account class trends
in the assignment of course grades (but only to increase grades).
- Extenuating circumstances will normally include only serious
emergencies or illnesses documented with a doctor's note.
- Students are responsible to make backups of all of their work! This
includes any assignment and other materials you produce.
- Students are responsible for the safe and ethical use of class
accounts on shared servers, according to university policy and
copyright law, and for the sole purpose of carrying out class assignments.
Accounts will be monitored and abuses will be reflected in the grades.
- See Resources for additional policies on use of computing, storage
and networking resources.
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Academic integrity
The principles of academic honesty and professional ethics will be
vigorously enforced in this course, following the IU Code of Student
Rights, Responsibilities, and Conduct and the CS Department
Statement on Academic Integrity.
This includes the usual standards on acknowledgment of help, contributions
and joint work, even when you are encouraged to build on libraries and
other software written by other people. Cases of academic misconduct
(including cheating, fabrication, plagiarism,
interference, or facilitating academic dishonesty) will not be tolerated.
Your submission of work to be graded in this class implies acknowledgement
of this policy. If you need clarification or have any questions, please see
the instructor during office hours.
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Final remarks
We would like to hear from anyone who has a disability
or other issues that may require some accommodations.
Please see the instructor after class or during office hours. The
DSS office and
Counseling
and Psychological Services (CAPS) are available for assistance to students.
We would like to know early in the semester of any possible
conflicts between course requirements/deadlines and
religious
or civic observances, so that accommodations can be made.
Please see the instructor after class or during office hours.
We welcome feedback on the class organization, material,
lectures, assignments and exams. You can provide us with constructive
criticism via the discussion forum. Please share your comments and
suggestions so that we can improve the class.
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