ANRL: Attributed Network Representation Learning via Deep Neural Networks
@inproceedings{Zhang2018ANRLAN, title={ANRL: Attributed Network Representation Learning via Deep Neural Networks}, author={Zhen Zhang and Hongxia Yang and Jiajun Bu and Sheng Zhou and Pinggang Yu and J. Zhang and M. Ester and C. Wang}, booktitle={IJCAI}, year={2018} }
Network representation learning (RL) aims to transform the nodes in a network into lowdimensional vector spaces while preserving the inherent properties of the network. [...] Key Method To capture the network structure, attribute-aware skipgram model is designed based on the attribute encoder to formulate the correlations between each node and its direct or indirect neighbors. We conduct extensive experiments on six real-world networks, including two social networks, two citation networks and two user behavior…Expand
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