Graph Mining, Spring 2020
Class Info   |   Resources   |   Schedule   |   Homeworks   |   Project

Class Info:

Syllabus
Meeting times: Monday and Thursday at 12-1:50pm in 3051 Low
No Class: Jan 20; Feb 17 => Yes class on Feb 18

Course Instructor:
Prof. George M. Slota
gmslota@gmail.com
Office Hours: Monday/Wednesday at 4-6pm in 317 Lally

Resources:

TextsPapersDatasets
NetworkX reference (v2.4)
Networks, Crowds, and Markets - Easly, Kleinburg (EK)
Network Science - Barabasi (B)
Mining of Massive Datasets - Leskovec, Rajaraman, Ullman (LRU) 		Thinking Like a Vertex
Graph Structure in the Web Revisited
Power-law distributions
Personalized PageRank
Link Prediction
Matrix Factorization 		Standford Large Network Dataset Collection
SuiteSparse Matrix Collection
Koblenz Network Collection
Laboratory for Web Algorithmics
Mark Newman's Collection
DIMACS Challenge Graphs
Index of Complex Network

Lecture Notes and Readings

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

WeekClass DateTopicReadingsNotes
1 13 Jan What is graph mining? Thinking Like a Vertex Lecture 1   |   Code   |   Data
16 Jan Graph connectivity and structure EK ch. 13   |   Graph Structure in the Web Revisited Lecture 2
2 20 Jan No class: MLK Day
23 Jan Network Measures EK ch. 18.2   |   Power-law distributions Lecture 3   |   Code   |   Data
3 27 Jan Centrality, Diffusion EK ch. 19, 21   |   Centrality Lecture 4   |   Code
30 Jan PageRank EK ch. 14   |   Personalized PageRank Lecture 5   |   Code   |   Data
4 3 Feb Social Networks Topics EK ch. 3, 4 Lecture 6   |   Code
6 Feb No class: Instructor Travel
5 10 Feb Link Prediction
13 Feb No class: Instructor Travel
6 17 18 Feb Link Prediction Unsupervised   |   Supervised Lecture 7   |   Code
20 Feb Recommender Systems Matrix Factorization   |   Netflix Prize   |   Dataset Lecture 8   |   Code
7 24 Feb Collaborative Filtering LRU ch. 9 Lecture 9   |   Code
27 Feb Community Detection B ch. 9 Lecture 10   |   Code
8 2 Mar Modularity Newman   |   Louvain   |   Resolution Limit Lecture 11   |   Code
5 Mar Project Proposal Presentations
9 9 Mar No class: Spring Break
12 Mar No class: Spring Break
10 16 Mar No class: Spring Break
19 Mar No class: Spring Break
11 23 Mar Spectral Clustering Implementation COVID update   |   Lecture 12   |   Code walkthrough   |   Code
26 Mar Community Evaluation B ch. 9   |   LFR Benchmark Econ update   |   Lecture 13   |   Code walkthrough   |   Code
12 30 Mar Contact Network Generation Modeling Overview Lecture 14
2 Apr Epidemiology Simulations Model Analysis SIR Analysis   |   Expanding our model
13 6 Apr Constructing a new COVID model Graph code   |   Simulation code   |   Experimentation   |   Exp. p2   |   Code
9 Apr Project Update Presentations Upload video via submitty forum
14 13 Apr Vertex labeling Node Classification Lecture 17
16 Apr Vertex Classification Description   |   Code Walkthrough   |   Code
15 20 Apr Graph Neural Networks GNN Model   |   GNN Types Lecture   |   COVID update 5
23 Apr Subgraph Mining Templates   |   Motifs   |   Graphlets 1   |   Graphlets 2   |   GRAAL Lecture
16 27 Apr Project Final Presentations
30 Apr Study Days: No class
4 May Project Final Submissions

Homeworks

Homeworks due at 11:59pm on the due date. No late homeworks will be accepted.

HW #Due DateHomeworkSolution
1 29 January 11:59pm HW 1 TBD
1 26 February 11:59pm HW 2 TBD

Project Info


Important Dates:

ItemDue DateDescription
Project Proposal 5 March In class
Update Presentation 9 April Via Submitty forum
Final Presentation 27 April Via Submitty forum
Final Report 4 May Via Submitty