Graph Mining, Spring 2026
Class Info   |   Resources   |   Schedule   |   Papers   |   Homeworks   |   Project

Class Info:

Syllabus
Meeting times: Monday and Thursday 12:00-1:50pm in Jonsson 3210
No Class: Jan 19; Feb 16 => Yes class on Feb 17
Last Class: April 27th


Course Instructor:
Prof. George M. Slota (slotag@rpi.edu)
Office Hours: Monday/Thursday at 2-3pm in 317 Lally
Webex: https://rensselaer.webex.com/meet/slotag

Resources:

TextsDatasets
NetworkX reference (v3.6.1)
Networks, Crowds, and Markets - Easly, Kleinburg (EK)
Network Science - Barabasi (B)
Mining of Massive Datasets - Leskovec, Rajaraman, Ullman (LRU) 		Standford Large Network Dataset Collection
SuiteSparse Matrix Collection
Koblenz Network Collection
Laboratory for Web Algorithmics
Mark Newman's Collection
DIMACS Challenge Graphs
Colorado Index of Complex Networks

Lecture Notes and Readings

Note: Class schedule subject to (and likely will) change.

WeekClass DateTopicReadingsNotes
1 12 Jan What is graph mining? Thinking Like a Vertex Notes   |   Code   |   Data
15 Jan Graph Connectivity and Structure EK ch. 13   |   Graph Structure in the Web   |   Revisited Notes   |   Code   |   Data 1   |   Data 2   |   Data Zebra
2 19 Jan MLK Day: No class
22 Jan Network Measures EK ch. 18.2   |   Power-law distributions Notes   |   Code   |   Data
3 26 Jan Snow Day
29 Jan Social Networks Topics EK ch. 3, 4 Notes   |   Code   |   Data
4 2 Feb Social Networks Continued EK ch. 3, 4 Notes   |   Code   |   Data
5 Feb Centrality EK ch. 19, 21   |   Centrality Notes   |   Code   |   Data 1   |   Data 2   |   Data 3
5 9 Feb PageRank EK ch. 14   |   Personalized PageRank Notes   |   Code   |   Data
12 Feb Intro to Learning on Graphs, Link Prediction Unsupervised   |   Supervised Notes   |   Code   |   Data
6 1617 Feb Project Proposal Presentations 1
19 Feb Project Proposal Presentations 2
7 23 Feb Collaborative Filtering Matrix Factorization   |   Netflix Prize   |   Dataset Notes   |   Code 1   |   Code 2   |   Data 1   |   Data 2
26 Feb Graph Neural Networks Model   |   Methods Notes   |   Code
8 2 Mar Spring Break
5 Mar Spring Break
9 9 Mar Community Detection and Clustering B ch. 9   |   Community Detection   |   Label Propagation Notes   |   Code   |   Data   |   Communities
12 Mar Modularity and Conductance Conductance   |   Newman   |   Louvain   |   Resolution Limit Notes   |   Code   |   Data   |   Communities
10 16 Mar Evaluating Community Detection LFR Benchmark Notes   |   Code   |   Data   |   Communities
19 Mar Spectral Graph Analysis Spectral Clustering Notes   |   Code   |   Data   |   Communities
11 23 Mar Project Update Presentations 1
26 Mar Project Update Presentations 2
12 30 Mar Vertex Labeling and Classification Node Classification Notes   |   Code   |   Data 1   |   2   |   3   |   4   |   5   |   6
2 Apr Random Graphs B ch. 3   |   Random Graphs   |   Chung Lu Notes
13 6 Apr Null Models Notes   |   Code   |   Data
9 Apr Subgraph Mining Motifs   |   Analytics Notes   |   Code   |   Data
14 13 Apr Graph Alignment Alignment   |   GRAAL Notes
16 Apr Parallel Graph Processing MPI   |   mpi4py Notes   |   Code
15 20 Apr Parallel Graph Processing Notes
23 Apr Final Project Presentations 1
16 27 Apr Final Project Presentations 2
29 Apr (3 May) Project Final Submissions Via Submitty

Homeworks

Homeworks due at MIDNIGHT EST on the due date, approximately two weeks after being released. Late homeworks will be accepted in accordance with the policy in the syllabus. Collaboration is allowed on homeworks.

HW #Due DateHomeworkTemplate
1 13 Feb HW 1 Template
2 13 Mar HW 2 Template
3 3 Apr HW 3 Template
4 17 Apr HW 4 Template
5 22 Apr HW 5 Template

Paper Presentations and Literary Reviews

You will be required to read and give short presentations on assigned papers (for 4280) or a longer literary review (for 6280). Below will be the list of papers and tentative dates to schedule both. THESE DATES WILL LIKELY CHANGE - ESPECIALLY THE ONES LATER IN THE SEMESTER

DateStudentPaper
26 Jan
29 Jan brooka9 Emergence of Scaling in Random Networks
2 Feb Patterns of Influence in a Recommendation Network
5 Feb ganesa4 Study on centrality measures in social networks: a survey
9 Feb hsuc3 Scaling Personalized Web Search
12 Feb lausem The Link Prediction Problem for Social Networks
23 Feb Link Prediction via Matrix Factorization
26 Feb matheb3 Link Prediction Based on Graph Neural Networks
9 Mar horlir Vertex Neighborhoods, Low Conductance Cuts, and Good Seeds for Local Community Methods
12 Mar hsuc3 Modularity and community structure in networks
16 Mar lausem Benchmark graphs for testing community detection algorithms
19 Mar horlir Spectral methods for graph clustering – A survey
30 Mar ganesa4 Graph neural networks in node classification: survey and evaluation
6 Apr matheb3 A Random Graph Model for Massive Graphs
9 Apr chanm10 Network Motifs: Simple Building Blocks of Complex Networks
13 Apr Survey of local and global biological network alignment: the need to reconcile the two sides of the same coin
16 Apr chanm10 From "Think Like a Vertex" to "Think Like a Graph"
20 Apr brooka9 Gunrock: A high-performance graph processing library on the GPU

Project Info



ItemDue DateDescription
Project Proposal 17, 19 February Proposal
Update Presentation 23, 26 March Update
Final Presentation 23, 27 April Final
Final Report 29 April Via Submitty