Towards Improving Embedding Based Models of Social Network Alignment via Pseudo Anchors

Last update: Nov 27, 2022

Related tags

Overview

PSML

paper: Towards Improving Embedding Based Models of Social Network Alignment via Pseudo Anchors

PSML_IONE,PSML_ABNE,PSML_DEEPLINK,PSML_SNNA:

numpy==1.14<br>
networkx==2.0<br>
scipy==0.19.1<br>
tensorflow>=1.12.1<br>
gensim==3.0.1<br>
scikit-learn==0.19.0<br>

PSML_DALUAP,PSML_MGCN:

python >= 3.6<br>
pytorch >= 0.4<br>
numpy  1.18.0<br>
tqdm<br>
networkx >2.0<br>

support data comes from :https://github.com/ChuXiaokai/CrossMNA
query data comes from :https://github.com/ColaLL/IONE
, https://github.com/ColaLL/AcrossNetworkEmbeddingDiversity

For PSML_IONE

   first run PSML_IONE.py
   second run Four.py
   getPrecision--should run emd_to_ione_emd.py and emd_to_ione_emd_t.py

For PSML_ABNE

   first run PSML_ABNE.py
   second run Four.py
   getPrecision--should run emd_to_ione_emd.py and emd_to_ione_emd_t.py

For PSML_SNNA

   use deepwalk or line get pre_data
   run PSML_SNNA.py

For PSML_DeepLink

   run embedding.py to use word2vec get pre_data
   run PSML_Deeplink.py

For PSML_MGCN

   run PSML_MGCN.py

For PSML_DALUAP

   run PSML_DALUAP.py

NOTE:

Method of adding pseudo node, Take two pseudo anchors, which are connected to each other, such as subnetwork file:

        node      node
         1          2
         3(anchor)  4

You need change it to:

        node      node
         1          2
         3(anchor)  4
         3          5(pse)
         3          6(pse)
         5(pse)     3
         6(pse)     3
         5(pse)     6(pse)
         6(pse)     5(pse)

Towards Improving Embedding Based Models of Social Network Alignment via Pseudo Anchors

Related tags

Overview

PSML

paper: Towards Improving Embedding Based Models of Social Network Alignment via Pseudo Anchors

For PSML_IONE

For PSML_ABNE

For PSML_SNNA

For PSML_DeepLink

For PSML_MGCN

For PSML_DALUAP

NOTE:

Owner

Code release for NeX: Real-time View Synthesis with Neural Basis Expansion

ULMFiT for Genomic Sequence Data

Official implementation of "Learning Proposals for Practical Energy-Based Regression", 2021.

Fully Convolutional DenseNets for semantic segmentation.

An Open-Source Tool for Automatic Disease Diagnosis..

Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields.

🧑‍🔬 verify your TEAL program by experiment and observation

Dados coletados e programas desenvolvidos no processo de iniciação científica

Official implementations of PSENet, PAN and PAN++.

A Distributional Approach To Controlled Text Generation

A comprehensive list of published machine learning applications to cosmology

Chinese Advertisement Board Identification(Pytorch)

Building Ellee — A GPT-3 and Computer Vision Powered Talking Robotic Teddy Bear With Human Level Conversation Intelligence

DFFNet: An IoT-perceptive Dual Feature Fusion Network for General Real-time Semantic Segmentation

ICCV2021 Oral SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks

Code for A Volumetric Transformer for Accurate 3D Tumor Segmentation

This program creates a formatted excel file which highlights the undervalued stock according to Graham's number.

Weakly-supervised object detection.

Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting

Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes (CVPR2021)