This repository contains the code used in our paper: MCR-Tree: An Efficient Index for Multi-dimensional Core Search. MCR-Tree projects graph vertices into a multi-dimensional space by leveraging the skyline property of cores, and integrates skyline coreness and connectivity information into an R-tree to facilitate the multi-dimensional core search..
We use 12 publicly available real-world networks, their types include directed graphs, bipartite graphs, and multilayer graphs. Directed graphs are obtained from SNAP and LAW. Bipartite graphs are obtained from KONECT. Multilayer graphs are obtained from Manlio De Domenico's Website.
An example format of the input data is shown in folder kl-core/test.
The following files are the codes for our proposed algorithms. Due to the inconsistent data format of different types of graphs, we split the code of the MCR-Tree into several different files. We implemented all codes the using C++ with CLion 2022.1.1.
- RStarTree.h : Algorithms to build R*-Tree [1].
- klSearch.cpp : Algorithms to construct MCR-Tree for the (k, l)-core and perform (k, l)-core saerch.
- abSearch.cpp : Algorithms to construct MCR-Tree for the (α, β)-core and perform (α, β)-core saerch.
- multilayerSearch.cpp : Algorithms to construct MCR-Tree for the multilayer k-core and perform multilayer k-core saerch.
- klUpdate.cpp, abUpdate.cpp, multilayerUpdate.cpp : Index maintenance algorithm of MCR-Tree.
[1] Beckmann N, Seeger B. A revised R*-tree in comparison with related index structures[C]//Proceedings of the 2009 ACM SIGMOD International Conference on Management of data. 2009: 799-812.
- Get skyline corenesses of the graph. Existing works [2] [3] can be used to perform core decomposition and get skylien corenesses for each vertex.
In the folder kl-core/test, test_degree.dat and test_graph.dat are the original graph, and test_klMax and test_skyline are files related to the skyline coreness.
- Build MCR-Tree and perform core search using Algorithms 1~3. There are two steps to build MCR-Tree: (i) build R-tree using skyline corenesses, (ii) compute contents of nodes for MCR-Tree.
For example, after the project is compiled, just type in:
/m-core/cmake-build-release/klSearch test
MCR-Tree of the test dataset is built and some core searches are performed.
[2] Fang Y, Wang Z, Cheng R, et al. Effective and efficient community search over large directed graphs[J]. IEEE Transactions on Knowledge and Data Engineering, 2018, 31(11): 2093-2107.
[3] Galimberti E, Bonchi F, Gullo F, et al. Core decomposition in multilayer networks: Theory, algorithms, and applications[J]. ACM Transactions on Knowledge Discovery from Data, 2020, 14(1): 1-40.
- cmake
- g++
- OpenMP