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allergic-rhinitis-na

Allergic rhinitics questionnaire data analysis via network approach

anomaly-detection-in-social-networks

Identify anomalies in social networks using graph embedding

assortativity

The algorithm to change the assortativity of networks

awesome-causality-algorithms

An index of algorithms for learning causality with data

awesome-complexity

A curated list of amazingly awesome Complexity Science resources, courses and shiny things

awesome-deep-community-detection

A Comprehensive Survey on Community Detection with Deep Learning

bimlpa

Community detection in bipartite networks

causal-discovery-from-nonstationary-heterogeneous-data

Causal Discovery from Nonstationary/Heterogeneous Data.

cbidoc

Cascading Behavior and Information Diffusion in Overlapping Clusters

cda2.0_tools

cdlib

Community Discovery Library - (for networkx and igraph)

clustering-glossary-terms-extracted-from-large-sized-software-requirements-using-fasttext

This repository contains the results of automatic glossary terms extraction and their clustering considering two important qualitative attributes, i.e. feature and benefit of the original CrowdRE requirement specifications dataset. In the original CrowdRE dataset, each entry has 6 attributes, i.e., role, feature, benefit, domain, tags and date-time of creation. Since, we are interested in extracting domain-specific terms from this dataset, we only focus on feature and benefit attributes of this dataset. The dataset used in our experiments containing only the feature and benefit attributes of the original CrowdRE dataset can be viewed in the file named "CrowdRE Requirements Dataset.csv". However, the original CrowdRE dataset is devloped by P. K. Murukannaiah et al. and can be accessed from "The smarthome crowd requirements dataset", https://crowdre.github.io/murukannaiah-smarthome-requirements-dataset/, April, 2017. We have computed and reported the ground truth set for a random subset of 100 requirement specifications of the used CrowdRE dataset. In total, we have manually identified a total of 120 ground truth glossary terms with 30 overlapping clusters. The ground truth glossary terms have been calculated from the best intuition of the people (s) involved in this project in an unbiased manner, as there exists no benchmark or gold standard related to the ground truth extraction and clustering for the CrowdRE dataset. The file named "Ground Truth Clusters.docx" shows the ground truth glossary terms along with the manually formulated semantically similar clusters. Note: the clusters are separated with (######) symbol in the file. Further, the manually identified 120 glossary terms in the ground truth set are shown in the third column of the file named as "Extracted Glossary Terms (With and Without WordNet Removal) and Ground Truth Glossary Terms.csv". We have extracted a total of 143 and 292 glossary terms from the CrowdRE dataset with or without removing some words specified in the WordNet lexical database (https://wordnet.princeton.edu/) using a mature text chunking approach. The results are shown in the first and second column of the file named "Extracted Glossary Terms (With and Without WordNet Removal) and Ground Truth Glossary Terms.csv". The extracted glossary terms are trained with the help of a domain specific corpora that is most related to used CrowdRE dataset, i.e. (Wikipedia Home Automation Category for a maximum depth of two, "https://en.wikipedia.org/wiki/Category:Home_automation") and with a pre-trained word vectors UMBC webbase corpus and statmt.org news dataset trained with subwords information in wikipedia 2017 (T. Mikolov, E. Grave, P. Bojanowski, C. Puhrsch, A. Joulin. Advances in Pre-Training Distributed Word Representations) using FastText word embedding vectors (https://fasttext.cc/docs/en/english-vectors.html). The main purpose of the training is to deduce the clusters by forming a the similarity matrix for the extracted glossary terms. For this, we have used two clustering algorithms, viz. K-Means and EM clustering algorithms. The similarity matrix have been developed using the computed semantic similarity scores (cosine similarity) between the word vectors using the word embedding based FastText model. The results in terms of automated formulated clusters for the random subset of 100 requirement specifications of the CrowdRE dataset for which the ground truth glossary terms are calculated are shown in the files named "Automated Ideal (Ground Truth) Clusters.docx" and "Automated Extraction and Clustering.docx" respectively. Note: there exists a maximum of n/2 clusters for n glossary terms. For evaluating the efficacy of the clustering algorithms, we used some commonly used performance evaluation metrics like (precision, recall, f-scores). The evaluation graphs utilizing the area under curve plots (AUC) and evaluating the normalized AUC scores for all the used clustering algorithms are trained on two different datasets and the evaluation results are shown in the two separate files namely, "Cluster Plots.docx" and "Extraction +Clustering Plots.docx" respectively.

community-detection-code

communityd

communitydetection

复杂网络社区发现算法、评价指标、常用数据集整理

communitydetectioncodes

Some overlapping community detection algorithms (Until 2016). by Yulin Che (https://github.com/CheYulin) for the PhD qualification exam (survey on community detection algorithms)

csns_netlogop

A Netlogo implementation of the Axelrod-Schelling model for cultural dissemination and segregation

cyber-space-to-physical-space

Code and Model Information for to support the paper: Yuan, X. and Crooks, A.T. (2017), From Cyber Space Opinion Leaders and the Spread of Anti-Vaccine Extremism to Physical Space Disease Outbreaks, SBP-BRIMS, pp. 114-119.

cycleratio

Data and Codes from the paper "Characterizing cycle structure in complex networks"

deep-learning-with-tensorflow-book

深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

defining_homographs

Use machine learning to determine the specific meaning from context of words that have multiple distinct meanings and usages.

demo

demo

dpp

DPPmodel and dataset

dynamicbenchmarkgenerator

Benchmark Generator for Dynamic Overlapping Communities

evo

network morphogenesis

flow-geometric-embedding-algorithm

The analytical and numerical flow distance on network.

flow_network_embedding

流网络嵌入——流距离词向量

fpc-sim

Fast Probabilistic Consensus Simulator

gcn

Implementation of Graph Convolutional Networks in TensorFlow

ggn

Gumbel Graph Network (GGN) : A General Deep Learning Framework for Network Reconstruction