lzrrr

lzrrr's Stars

• chaihahaha/incGM

  reproduce incGM+

  Language:Python1

• dccspeed/fractal

  Language:Scala288

• kahypar/kahypar

  KaHyPar (Karlsruhe Hypergraph Partitioning) is a multilevel hypergraph partitioning framework providing direct k-way and recursive bisection based partitioning algorithms that compute solutions of very high quality.

  Language:C++42091

• KaHIP/KaHIP

  KaHIP -- Karlsruhe HIGH Quality Partitioning.

  Language:C++38495

• KarypisLab/METIS

  METIS - Serial Graph Partitioning and Fill-reducing Matrix Ordering

  Language:C668136

• KarypisLab/ParMETIS

  ParMETIS - Parallel Graph Partitioning and Fill-reducing Matrix Ordering

  Language:C10642

• ehab-abdelhamid/ScaleMine

  Parallel Frequent Subgraph Mining

  Language:C++2812

• zakimjz/DistGraph

  Distributed Graph Mining on a Massive "Single" Graph

  Language:C++135

• qcri/Arabesque

  Scalable Graph Mining

  Language:Java6133

• anilpacaci/streaming-graph-partitioning

  Experimental Setup for Performance Analysis of Streaming Algorithms

  Language:Groovy304

• ehab-abdelhamid/GraMi

  GraMi is a novel framework for frequent subgraph mining in a single large graph, GraMi outperforms existing techniques by 2 orders of magnitudes. GraMi supports finding frequent subgraphs as well as frequent patterns, Compared to subgraphs, patterns offer a more powerful version of matching that captures transitive interactions between graph nodes (like friend of a friend) which are very common in modern applications. Also, GraMi supports user-defined structural and semantic constraints over the results, as well as approximate results. For more details, check our paper: Mohammed Elseidy, Ehab Abdelhamid, Spiros Skiadopoulos, and Panos Kalnis. GRAMI: Frequent Subgraph and Pattern Mining in a Single Large Graph. PVLDB, 7(7):517-528, 2014.

  Language:Java10739