bioinformatics scikit-learn chemoinformatics graph-mining graph-kernels graph-similarity-algorithms graph-classification graph-similarity Updated Dec 23, 2020 Python danielzuegner / nettack Star 153 Code Issues Pull requests Implementation of the paper "Adversarial Attacks on Neural Networks for Graph ...
Anomaly Mining - Past, Present and Future Graph Computing for Financial Crime and Fraud Detection: Trends, Challenges and Outlook Graph-based anomaly detection and description: a survey Adversarial Attack and Defense on Graph Data: A Survey Suspicious behavior detection: Current trends and future direc...
Computer science A graph-based approach for semantic data mining UNIVERSITY OF OREGON Dejing Dou LiuHaishanData mining is the nontrivial extraction of implicit, previously unknown, and potentially useful information from data. It is widely acknowledged that the role of domain knowledge in the ...
Semantic Variations: These refer to phrases with synonymous vocabulary but varied linguistic expressions. For instance: [‘Dry Reforming Of Methane’, ‘Dry Reforming Of Methane Reaction’], [‘Light-Harvesting Ability’, ‘Light-Harvesting Capability’] 3. Non-ASCII Entities: These consist of spec...
We combine several graph alignment features with lexical semantic similarity measures using machine learning techniques and show that the student answers can be more accurately graded than if the semantic measures were used in isolation. We also present a first attempt to align the dependency graphs ...
VERSE: Versatile Graph Embeddings from Similarity Measures Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Emmanuel Müller WWW 2018 Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, Jie Tang ...
Graph similarity learning, which measures the similarities between a pair of graph-structured objects, lies at the core of various machine learning tasks such as graph classification, similarity search, etc. In this paper, we devise a novel graph neural network based framework to address this chall...
A semantic graph is built on semantic similarity and relatedness measures. • A novel Edge-gated GCN is proposed to explore multi-channel edge features. • A new sub-objective loss function of semantic information is considered. Abstract ...
GemsLab / MCbook_Individual-Collective_GraphMining Star 19 Code Issues Pull requests Slides and code for the Morgan Claypool book on "Individual and Collective Graph Mining: Principles, Algorithms and Applications" code networks belief-propagation network-alignment dynamic-networks graph-similarity tuto...
To indicate the strength of the semantic relationships between nodes and edges, we introduce weight 𝑤𝑖𝑗wij of the edge connecting 𝑣𝑖vi and 𝑣𝑗vj. The weight computation is based on different similarity measures, like cosine similarity [29], Jaccard similarity [30], and semantic...