Home

Awesome

STWalk

This repository contains implementation of STWalk: Learning Trajectory Representations in Temporal Graphs.

STWalk uses structural properties of graphs at present and previous time-steps to capture the spatio-temporal behavior of nodes. There are two variants of STWalk:

Supriya Pandhre, Himangi Mittal, Manish Gupta and Vineeth N Balasubramanian STWalk: Learning Trajectory Representations in Temporal Graphs

Requirement

To run the STWalk1 algorithm:

Please use --dataset <dataset-name> argument, where dataset-name can be one of the following: "dblp", "epinion", "ciao". By default the code will be executed on Epinion dataset. The output will be saved in /epinion/output_stwalkone/ folder

cd code
python STWalk1.py --dataset epinion

To run the STWalk2 algorithm:

The output will be saved in /ciao/output_stwalktwo/ folder

cd code
python STWalk2.py --dataset ciao

Data

We experiment on three real-world datasets: DBLP, Epinion, Ciao datasets

Cite

Please cite our paper if you use this code in your work:

Paper title: STWalk: Learning Trajectory Representations in Temporal Graphs

Link: https://arxiv.org/abs/1711.04150

Authors: Supriya Pandhre, Himangi Mittal, Manish Gupta, Vineeth N Balasubramanian