swMATH ID: 27202
Software Authors: Aditya Grover, Jure Leskovec
Description: node2vec: Scalable Feature Learning for Networks. Prediction tasks over nodes and edges in networks require careful effort in engineering features used by learning algorithms. Recent research in the broader field of representation learning has led to significant progress in automating prediction by learning the features themselves. However, present feature learning approaches are not expressive enough to capture the diversity of connectivity patterns observed in networks. Here we propose node2vec, an algorithmic framework for learning continuous feature representations for nodes in networks. In node2vec, we learn a mapping of nodes to a low-dimensional space of features that maximizes the likelihood of preserving network neighborhoods of nodes. We define a flexible notion of a node’s network neighborhood and design a biased random walk procedure, which efficiently explores diverse neighborhoods. Our algorithm generalizes prior work which is based on rigid notions of network neighborhoods, and we argue that the added flexibility in exploring neighborhoods is the key to learning richer representations. We demonstrate the efficacy of node2vec over existing state-of-the-art techniques on multi-label classification and link prediction in several real-world networks from diverse domains. Taken together, our work represents a new way for efficiently learning state-of-the-art task-independent representations in complex networks.
Homepage: https://arxiv.org/abs/1607.00653
Source Code:  https://github.com/aditya-grover/node2vec
Related Software: DeepWalk; LINE; word2vec; GraRep; Adam; t-SNE; PyTorch; struc2vec; GloVe; Scikit; metapath2vec; LIBLINEAR; SNAP; ImageNet; Tensor2Tensor; GitHub; TensorFlow; graph2vec; ArnetMiner; DynGEM
Cited in: 119 Documents
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Cited by 430 Authors

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Cited in 41 Serials

17 Information Sciences
12 Data Mining and Knowledge Discovery
10 Machine Learning
9 Physica A
5 Neural Networks
5 INFORMS Journal on Computing
4 Journal of Machine Learning Research (JMLR)
4 Journal of Statistical Mechanics: Theory and Experiment
3 Mathematical Biosciences and Engineering
3 Computer Science Review
2 Physics Reports
2 Applied Mathematics and Computation
2 Computing
2 Journal of the American Statistical Association
2 SIAM Review
2 Journal of Combinatorial Optimization
2 Parallel Processing Letters
1 Artificial Intelligence
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1 Discrete Applied Mathematics
1 Discrete Mathematics
1 Journal of Mathematical Biology
1 Mathematical Biosciences
1 The Annals of Statistics
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1 Theoretical Computer Science
1 SIAM Journal on Applied Mathematics
1 Journal of Mathematical Imaging and Vision
1 Computational and Applied Mathematics
1 The Journal of Artificial Intelligence Research (JAIR)
1 Journal of Applied Statistics
1 International Journal of Wavelets, Multiresolution and Information Processing
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