ECE 4502/6502 & CS 6501: Graph Mining (Spring 2021)

Course Logistics

  • Class Location: Online

  • Class Time: Tuesday and Thursday 3:30PM - 4:45PM

  • Collab (for lecture slides and recorded videos)

  • Piazza (for class Q&A)

Important Note: All lectures will be held at the scheduled time on Zoom. Students can find the Zoom links on Collab, under the Online Meetings tab. The lecture videos will also be uploaded into Collab to accommodate students at different time zones.

Course Description

Graphs/networks are often used to represent a plethora of real-world phenomena: social relations among online users, hyperlinks among webpages, biological interactions among genes, brain activities among neurons, to name a few. How can we understand, characterize, and extract actionable knowledge from the deluge of graph data, to benefit high-impact applications from different disciplines? This course will introduce the fundamental problems and cover the recent research advances in analyzing and mining large-scale graphs. It will also discuss the practical applications and the broad impacts of graph mining algorithms in diverse settings (e.g., social media, e-commerce, education, and security). The following topics will be covered in the course: graph essentials, network measures, network models, data mining essentials, community analysis, information diffusion, recommendation, network representation learning, and graph neural networks.


There are no official prerequisites for this course, but students are expected to:

  • have basic knowledge about data mining and machine learning

  • be familiar with linear algebra, discrete mathematics, and statistics

  • be comfortable to read research papers and give presentations

  • have good programming skills, e.g, Python, C/C++, Java, Matlab, and R.

Textbooks and Other Resources

Schedule (Tentative)

Week Date Content Event Due
1 02/02 Introduction to Graph Mining
02/04 Graph Essentials I
2 02/09 Graph Essentials II
02/11 Network Measures I
3 02/16 Course Projects & Network Measures II HW1 Out
02/18 Network Measures III & Network Models I
4 02/23 Network Models II
02/25 Network Models III
5 03/02 Data Mining Essentials I
03/04 Data Mining Essentials II Project Proposal Report Due
6 03/09 Break Day (No Class)
03/11 Data Mining Essentials III & Community Analysis I HW1 Due
7 03/16 Community Analysis II
03/18 Community Analysis III
8 03/23 Information Diffusion I HW2 Out
03/25 Information Diffusion II
9 03/30 Recommendation I
04/01 Recommendation II
10 04/06 Take-Home Midterm Exam
04/08 Graph Embedding HW2 Due (April 11)
11 04/13 Graph Neural Networks I Project Progress Report Due (April 13)
04/15 Break Day (No Class)
12 04/20 Graph Neural Networks II
04/22 Paper presentation
13 04/27 Paper Presentation
04/29 Paper Presentation
14 05/04 Paper Presentation
05/06 Paper Presentation Project Final Report Due on May 9th

Grading Policy

  • Homework assignment: 40%

    • There will be 2 homework assignment and each homework is worth 20%.

    • Each homework consists of written questions and programming questions, and only electronic submission is allowed.

    • All assignments follow the “no-late” policy. Assignments received after the due time (11:59pm on the due day) will receive zero credit.

  • Take-home midterm exam: 15%

  • Paper Presentation: 15%

    • We will provide a list of suggested papers in top venues.

    • The presentation will be graded by the instructor and the TA.

    • The slides of your presentation need to be sent to the instructor and TA by 11:59PM the night before your presentation.

    • The grading will be based on the clarity, content, critiques and insightful comments, timing, and handling of questions.

  • Project: 30%

    • Teams with only graduate students: 1~2 people; Teams with undergrdatuate students: 1~3 people.

    • Students are expected to investigate a research problem related to graph mining and ideally related to their own research.

    • You need to deliver the following for your project:

      • Project Proposal Report (5%)

      • Project Progress Report (5%)

      • Project Report (20%)

      • All the reports follow the “no-late” policy

Grading Rubric

Grade cutoff points: A+ [97, 100]; A [93, 97); A- [90, 93); B+ [87, 90); B [83, 87); B- [75, 83); C+ [65, 75); C [60, 65); F [0, 60)

Other Related Statements

Honor Code (Adapted from Honor Syllabus Example Statement of UVa)

I trust every student in this course to fully comply with all of the provisions of the University’s Honor Code. By enrolling in this course, you have agreed to abide by and uphold the Honor System of the University of Virginia, as well as the policies specific to this course. All suspected violations will be forwarded to the Honor Committee, and you may, at my discretion, receive an immediate zero on that assignment regardless of any action taken by the Honor Committee.

Please let me know if you have any questions regarding the course honor policy. If you believe you may have committed an Honor Offense, you may wish to file a Conscientious Retraction by calling the Honor Offices at (434) 924-7602. For your retraction to be considered valid, it must, among other things, be filed with the Honor Committee before you are aware that the act in question has come under suspicion by anyone. More information can be found at

Students with Disabilities or Special Needs

Please contact the instructor at the beginning of the semester. The University of Virginia strives to provide accessibility to all students. If you require an accommodation to fully access this course, please contact the Student Disability Access Center (SDAC) at (434) 243-5180 or If you are unsure if you require an accommodation, or to learn more about their services, you may contact the SDAC at the number above or by visiting their website at

Violence Prevention and Sexual Assault Prevention

The University of Virginia is dedicated to providing a safe and equitable learning environment for all students. To that end, it is vital that you know two values that I and the University hold as critically important:

  • Power-based personal violence will not be tolerated.

  • Everyone has a responsibility to do their part to maintain a safe community on Grounds.

If you or someone you know has been affected by power-based personal violence, more information can be found on the UVA Sexual Violence website that describes reporting options and resources available -

As your professor and as a person, know that I care about you and your well-being and stand ready to provide support and resources as I can. As a faculty member, I am a responsible employee, which means that I am required by University policy and federal law to report what you tell me to the University's Title IX Coordinator. The Title IX Coordinator's job is to ensure that the reporting student receives the resources and support that they need, while also reviewing the information presented to determine whether further action is necessary to ensure survivor safety and the safety of the University community. If you would rather keep this information confidential, there are Confidential Employees you can talk to on Grounds (See The worst possible situation would be for you or your friend to remain silent when there are so many here willing and able to help.

Religious Accommodations

It is the University's long-standing policy and practice to reasonably accommodate students so that they do not experience an adverse academic consequence when sincerely held religious beliefs or observances conflict with academic requirements. Students who wish to request academic accommodation for a religious observance should submit their request in writing directly to me by email as far in advance as possible. Students and instructors who have questions or concerns about academic accommodations for religious observance or religious beliefs may contact the University’s Office for Equal Opportunity and Civil Rights (EOCR) at or 434-924-3200. Accommodations do not relieve you of the responsibility for completion of any part of the coursework missed as the result of a religious observance.

Recording of Classroom Activities

I will be recording every lecture in order to accommodate students who will be learning remotely. Because lectures include fellow students, you and they may be personally identifiable on the recordings. These recordings may only be used for the purpose of individual or group study with other students enrolled in this class during this semester. You may not distribute them in whole or in part through any other platform or to any persons outside of this class, nor may you make your own recordings of this class unless written permission has been obtained from the Instructor and all participants in the class have been informed that recording will occur. If you want additional details on this, please see Provost Policy 008 which is expected to be updated for the Fall 2020 semester. If you notice that I have failed to activate the recording feature, please remind me!