Python Implementation of algorithms in Graph Mining, e.g., Recommendation, Collaborative Filtering, Community Detection, Spectral Clustering, Modularity Maximization, co-authorship networks.

Last update: Mar 03, 2022

Overview

Graph Mining

Author: Jiayi Chen

Time: April 2021

Implemented Algorithms:

Network:
- Scrabing Data, Network Construbtion and Network Measurement (e.g., Pagerank, clustering coefficient, ...)
Recommendation:
- User-based Collaborative Filtering
- Item-based Collaborative Filtering
Community Detection:
- Spectral clustering algorithm
- Modularity maximization algorithm

Requirements

python 3
networkx
pandas

Getting Started

Scrabing Data & Network Construbtion & Measurement

run "/graph_scraping_construction_measurement/main.py"

Collaborative Filtering

run "/collaborative_filtering/main.py"

User-based collaborative filtering: "/collaborative_filtering/user_based_CF.py"
Item-based collaborative filtering: "/collaborative_filtering/item_based_CF.py"

Community Detection

Community number is set to k=2.

run "/community_detection/main.py"

Spectral clustering: /community_detection/spectral_clustering.py
modularity maximization: /community_detection/modularity_maximization.py
Result example:

Python Implementation of algorithms in Graph Mining, e.g., Recommendation, Collaborative Filtering, Community Detection, Spectral Clustering, Modularity Maximization, co-authorship networks.

Related tags

Overview

Graph Mining

Implemented Algorithms:

Requirements

Getting Started

Scrabing Data & Network Construbtion & Measurement

Collaborative Filtering

Community Detection

Owner

Jiayi Chen

Pytorch implementation of "Neural Wireframe Renderer: Learning Wireframe to Image Translations"

ViewFormer: NeRF-free Neural Rendering from Few Images Using Transformers

OREO: Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning (NeurIPS 2021)

Large-scale Hyperspectral Image Clustering Using Contrastive Learning, CIKM 21 Workshop

Episodic Transformer (E.T.) is a novel attention-based architecture for vision-and-language navigation. E.T. is based on a multimodal transformer that encodes language inputs and the full episode history of visual observations and actions.

Voxel-based Network for Shape Completion by Leveraging Edge Generation (ICCV 2021, oral)

Embeddinghub is a database built for machine learning embeddings.

Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22)

Recurrent Neural Network Tutorial, Part 2 - Implementing a RNN in Python and Theano

Hough Transform and Hough Line Transform Using OpenCV

Code release for "COTR: Correspondence Transformer for Matching Across Images"

[CVPR2021] Look before you leap: learning landmark features for one-stage visual grounding.

Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling"

Official code of CVPR 2021's PLOP: Learning without Forgetting for Continual Semantic Segmentation

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

codes for paper Combining Dynamic Local Context Focus and Dependency Cluster Attention for Aspect-level sentiment classification

Official Code for "Non-deep Networks"

PROJECT - Az Residential Real Estate Analysis

The official implementation of our CVPR 2021 paper - Hybrid Rotation Averaging: A Fast and Robust Rotation Averaging Approach

DockStream: A Docking Wrapper to Enhance De Novo Molecular Design