Hypergraph Core Decomposition Source Code

The HypergraphKCore tool is designed for analyzing and manipulating hypergraphs through various operations including k-core decomposition, sorting, and generating hypergraphs with specific distributions.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

Before building the HypergraphKCore tool, ensure you have CMake installed on your system. You can download it from https://cmake.org/download/ or install it using a package manager for your operating system.

If you are using Max OS X, you need to install the llvm to allow the omp library to work properly. You can install it using Homebrew:

brew install llvm

Suggested IDE

We recommend using CLion as the IDE for this project. You can download it from https://www.jetbrains.com/clion/download/.

Building the Project

To build the project, follow these steps:

1. Clone the repository to your local machine.

git clone [email protected]:unswdb/hyper-k-core.git

2. Navigate to the root directory of the project.

cd hyper-k-core

3. Create a new directory for the build:

mkdir build

4. Run CMake to configure the project:

cmake -S . -B ./build -DCMAKE_BUILD_TYPE=Release

5. Compile the project:

cmake --build ./build

This will create the HypergraphKCore executable within the build directory.

Usage

To use the HypergraphKCore tool, run the executable from the command line by specifying a dataset and the desired operation. The basic syntax is:

./build/HypergraphKCore <datasets> [options]

Options

• info : Get graph information.
• detail : Get graph details and write to <dataset>.{_nbrs,_edges,_degree}.
• org : Organize nodes, renumbering them from 1 to N, remove duplicates nodes in the same hyperedge, remove empty hyperedges or single-node hyperedges, the output will overwrite the original dataset.
• vary : Vary nodes, generate 20%, 40%, 60%, 80%, and 100% of the original hypergraph, the output will be written to <dataset>_{20,40,60,80,100}.hyp.
• sort <degree|nbr> <asc|desc> : Sort nodes by degree or neighbors in ascending or descending order by renumbering nodes.
• gen (P | W) (nbr | deg) <numNodes> <numEdges> : Generate an organized hypergraph with a PowerLaw (P) or Weibull (W) distribution.
  • P : PowerLaw distribution.
  • W : Weibull distribution.
  • nbr : distribution neighbors.
  • deg : distribution degree.
  • <numNodes> : Number of nodes.
  • <numEdges> : Number of edges.
• (0-5) : Run single thread k-core decomposition with the specified algorithm.
  • 0 - HyperCD* The Most efficient algorithm.
  • 1 - HyperCD+ with RUC
  • 2 - HyperCD+ with LB
  • 3 - HyperCD+
  • 4 - HyperCD
  • 5 - HyperCD++
• 10 <numThreads> : Run multi-thread k-core decomposition with the specified number of threads.

Important:

Before running any other operation, run ./build/HypergraphKCore <dataset> org to organize the hypergraph.

Examples

To get the graph information of dataset.hyp:

./build/HypergraphKCore datasets.hyp info

To run k-core decomposition with the HyperCD* algorithm:

./build/HypergraphKCore datasets.hyp 0

To generate a graph with a PowerLaw distribution of neighbor size, 1000 nodes, and 5000 edges:

./build/HypergraphKCore output.hyp gen P nbr 1000 5000

For further details on options and their usage, run the tool with the --help option:

./build/HypergraphKCore --help

Dataset File Format

The dataset file expected by the HypergraphKCore tool should be structured where each line represents a hyperedge. Each line contains a list of node identifiers, separated by commas, indicating that these nodes are part of the same hyperedge. For example, a line like 1,2,3,4,5 signifies that a hyperedge containing nodes 1, 2, 3, 4, and 5. This format allows the representation of complex connectivity patterns within the hypergraph, enabling the tool to accurately perform its analyses and manipulations based on the input dataset.

Example Usage

We provide a shell script main_run.sh to run the experiments in the paper. The simple dataset coauth-MAG-History-full.hyp is provided in the /dataset directory.

License

This project is licensed under the MIT License - see the LICENSE.txt file for details.