Implementation of NEP, ICDM 2019.

Please cite the following work if you find the code useful.

@inproceedings{yang2019neural,
	Author = {Yang, Carl and Zhang, Jieyu and Han, Jiawei},
	Booktitle = {ICDM},
	Title = {Neural embedding propagation on heterogeneous networks},
	Year = {2019}
}

Contact: Carl Yang (yangji9181@gmail.com)

Inputs

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See data.zip as am example.

Command

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To train NEP model with default setting, please first unzip data.zip and then run

python3 nep/main.py

You can specify the parameters. The variable names are self-explaining.

Key Parameters

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dataset: the path to data folder should be ./data/dataset.

target_node_type: should be consistent with the node type in node.dat file, in example dblp-sub dataset, the target node type is 'a'.

train_ratio: how many of labeled data to be used as train data.

superv_ratio: how many of train data to be exposed to model (used in experiment of label efficiency).

path_max_length: the maximum length of a pattern (used in the experiment of path length).