TS-Extractor: Large Graph Exploration Via Subgraph Extraction Based on Topological and Semantic Information

An interactive graph visualization system to enable users to extract, analyze and expand relevant subgraphs.

Demo video: Please see the file "TS-Extractor.mp4"

Our input is a large graph that contains thousands or more nodes and has node attributes (i.e., semantic information).

The major goal of this project is to help the user explore a large graph by extracting a subgraph (context) relevant to the user-specified nodes (called focus nodes). The extracted subgraph should contain as many nodes sharing the same/similar attribute values with the focus nodes as possible, which can provide the user with clear semantics.

Setup

It is recommended to install this system in the ubuntu system.

Server

1. To install the dependency packages of the system server, under the project dir "Server", run:

pip install -r requirements.txt

2. Under the project dir "Server/DB", Unzip the database files.

3. Run the file "Vue_Flask_App.py".

FrontEnd

1. Install Node.js.

2. To install the dependency packages of the system frontend, under the project dir "FrontEnd", run:

npm install

3. Under the project dir "FrontEnd", run:

Sudo npm run dev

4. Access the system interface at http://localhost:8080.

Citation

Please consider citing our paper in your publications if the project helps your research. BibTeX reference is as follows:

@Article{Fu2020TSExtractorLG,
  Title                    = {TS-Extractor: large graph exploration via subgraph extraction based on topological and semantic information},
  Author                   = {Kun Fu and Tingyun Mao and Yang Wang and Daoyu Lin and Y. Zhang and Junjian Zhan and Xi-an Sun and F. Li},
  Journal                  = {Journal of Visualization},
  Year                     = {2020},
  Pages                    = {1 - 18} 
}