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Search results for graph data mining

28 search results found

Graph Fraud Detection Papers ⭐ 1,148

A curated list of graph-based fraud, anomaly, and outlier detection papers & resources

Awesome Fl ⭐ 1,103

Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

Graph Adversarial Learning Literature ⭐ 772

A curated list of adversarial attacks and defenses papers on graph-structured data.

Dgfraud ⭐ 432

A Deep Graph-based Toolbox for Fraud Detection

Awesome Deep Community Detection ⭐ 397

Deep and conventional community detection related papers, implementations, datasets, and tools.

Deepgraph ⭐ 274

Analyze Data with Pandas-based Networks. Documentation:

Awesome Deep Graph Anomaly Detection ⭐ 215

Awesome graph anomaly detection techniques built based on deep learning frameworks. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in anomaly detection, graph representation learning, and graph anomaly detection to join this project as contributors and boost further research in this area.

Care Gnn ⭐ 127

Code for CIKM 2020 paper Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters

Python toolbox to evaluate graph vulnerability and robustness (CIKM 2021)

pathpy is an OpenSource python package for the modeling and analysis of pathways and temporal networks using higher-order and multi-order graphical models

Socialite ⭐ 99

SociaLite: query language for large-scale graph analysis and data mining

Source code for EvalNE, a Python library for evaluating Network Embedding methods.

Graph_sampling ⭐ 89

Graph Sampling is a python package containing various approaches which samples the original graph according to different sample sizes.

`Slib` is a JAVA library dedicated to semantic data mining based on texts and/or ontology processing. The library is composed of various modules dedicated to specific treatments - they can be used in the context of information retrieval, data analysis, recommendation system design... The Semantic Measures Library (SML) is a sub-project of the Slib.

Python implementation of frequent subgraph mining algorithm gSpan. Directed graphs are supported.

Crystal Graph Neural Networks

Graph Pattern Learner ⭐ 71

Evolutionary Graph Pattern Learner that learns SPARQL queries for a given set of source-target-pairs from an endpoint.

Bookworm ⭐ 54

📚 social networks from novels

Spartan2 ⭐ 50

A collection of data mining algorithms on big graphs and time series

Network Embedding Resources ⭐ 41

Network Embedding Survey and Resources

The reference implementation of FEATHER from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models".

Malnet Graph ⭐ 27

A large-scale database for graph representation learning

Telegram Groups Crawler ⭐ 25

A Telegram crawler made in Python to automatically search groups and channels and collect any type of data from them.

Rdfrules ⭐ 23

RDFRules: Analytical Tool for Rule Mining from RDF Knowledge Graphs

The Subdue graph miner discovers highly-compressing patterns in an input graph.

Resolutions 2019 ⭐ 16

A list of data mining and machine learning papers that I implemented in 2019.

Bitcoin Address Behavior Analysis ⭐ 14

Wikibrain ⭐ 11

Wikipedia graph mining: dynamic structure of collective memory

R Ghypernet ⭐ 9

R package for Generalised Hypergeometric Ensembles of Random Graphs (gHypEG)

Semistructured Multilayer Document Model

A miner to do a sociological data-mining from vk.com

Nestedsubtreehash ⭐ 7

A distributed implementation of "Nested Subtree Hash Kernels for Large-Scale Graph Classification Over Streams" (ICDM 2012).

Datamining ⭐ 7

This repository contains the implementation of certain data mining algorithms and sample programs of data science tools

Myr Languagecodes ⭐ 7

My efforts for bettering my knowlage of R language

Snowballsampling ⭐ 6

This is an example of LiveJournal Data Mining using the Snowball Sampling Method.

Code & experiments for MINDWALC: Mining Interpretable, Discriminative Walks for Classification of Nodes in a Graph

gSpan, an efficient algorithm for mining frequent subgraphs

Anomaly Detection ⭐ 5

Anomaly detection in time-series networks. Spatio-temporal Anomaly Detection

graph-based substructure pattern mining algorithm (authors: Xifeng Yan, Jiawei Han) implementation

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