Spring 2022 - CMPT 984 G100

Special Topics in Databases, Data Mining, Computational Biology (3)

Scalable Graph Mining Techniques

Class Number: 7988

Delivery Method: In Person


  • Course Times + Location:

    Fr 2:30 PM – 5:20 PM
    SWH 10041, Burnaby



This is a seminar-style special topics course on recent advances in graph analytics and management systems. Modern data analytics solutions (machine learning, data mining, etc.) often involve graph-based computations to infer useful results. The growing need of analyzing graph data, coupled with the rapid increase in the amount of graph data to be analyzed has led to the development of various large-scale graph analytics systems. Developing these systems requires careful design of fundamental components like graph data structures, concurrent execution models, scalable graph algorithms, as well as generic programming models. In this course, we will focus on scalable solutions and systems for emerging graph mining applications. We will explore how challenges in mining large graphs are being solved in real-world systems as well as the limitations inherent in their designs. This is a seminar-style course, meaning that students are expected to give presentations on research papers. Background in software systems, databases and parallel computing is preferable.


  • Graph mining applications and their challenges
  • Execution models
  • Programming models
  • Processing static and dynamic graphs
  • Graph mining across different execution environments (e.g. shared memory, distributed, etc.)



To be discussed in the first week of class.

Graduate Studies Notes:

Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.

Registrar Notes:


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Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html


Teaching at SFU in spring 2022 will involve primarily in-person instruction, with safety plans in place.  Some courses will still be offered through remote methods, and if so, this will be clearly identified in the schedule of classes.  You will also know at enrollment whether remote course components will be “live” (synchronous) or at your own pace (asynchronous).

Enrolling in a course acknowledges that you are able to attend in whatever format is required.  You should not enroll in a course that is in-person if you are not able to return to campus, and should be aware that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes.

Students with hidden or visible disabilities who may need class or exam accommodations, including in the context of remote learning, are advised to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112) as early as possible in order to prepare for the spring 2022 term.