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[PR #259] [MERGED] Added Karate Club an unsupervised machine learning for graphs #270

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opened 2025-11-06 17:15:55 -06:00 by GiteaMirror · 0 comments
GiteaMirror commented 2025-11-06 17:15:55 -06:00
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📋 Pull Request Information

Original PR: https://github.com/oxnr/awesome-bigdata/pull/259
Author: @benedekrozemberczki
Created: 1/25/2020
Status: ✅ Merged
Merged: 2/4/2020
Merged by: @vincentkoc

Base: master ← Head: patch-1

📝 Commits (1)

  • c06a444 Added Karate Club an unsupervised machine learning for graphs

📊 Changes

1 file changed (+1 additions, -0 deletions)

View changed files

📝 README.md (+1 -0)

📄 Description

Karate Club consists of state-of-the-art methods to do unsupervised learning on graph structured data. To put it simply it is a Swiss Army knife for small-scale graph mining research. First, it provides network embedding techniques at the node and graph level. Second, it includes a variety of overlapping and non-overlapping community detection methods. Implemented methods cover a wide range of network science (NetSci, Complenet), data mining (ICDM, CIKM, KDD), artificial intelligence (AAAI, IJCAI) and machine learning (NeurIPS, ICML, ICLR) conferences, workshops, and pieces from prominent journals.

🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.

## 📋 Pull Request Information **Original PR:** https://github.com/oxnr/awesome-bigdata/pull/259 **Author:** [@benedekrozemberczki](https://github.com/benedekrozemberczki) **Created:** 1/25/2020 **Status:** ✅ Merged **Merged:** 2/4/2020 **Merged by:** [@vincentkoc](https://github.com/vincentkoc) **Base:** `master` ← **Head:** `patch-1` --- ### 📝 Commits (1) - [`c06a444`](https://github.com/oxnr/awesome-bigdata/commit/c06a4444eb44a9d89bad1c112de6b00376c5a81a) Added Karate Club an unsupervised machine learning for graphs ### 📊 Changes **1 file changed** (+1 additions, -0 deletions) <details> <summary>View changed files</summary> 📝 `README.md` (+1 -0) </details> ### 📄 Description Karate Club consists of state-of-the-art methods to do unsupervised learning on graph structured data. To put it simply it is a Swiss Army knife for small-scale graph mining research. First, it provides network embedding techniques at the node and graph level. Second, it includes a variety of overlapping and non-overlapping community detection methods. Implemented methods cover a wide range of network science (NetSci, Complenet), data mining (ICDM, CIKM, KDD), artificial intelligence (AAAI, IJCAI) and machine learning (NeurIPS, ICML, ICLR) conferences, workshops, and pieces from prominent journals. --- <sub>🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.</sub>
GiteaMirror added the pull-request label 2025-11-06 17:15:55 -06:00
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Reference: github-starred/awesome-bigdata#270
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