Source code for AAAI 2019 paper "Relation Structure-Aware Heterogeneous Information Network Embedding"
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Python 2.7
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numpy
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scipy
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PyTorch (0.3.0)
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My machine with two GPUs (NVIDIA GTX-1080 *2) and two CPUs (Intel Xeon E5-2690 * 2)
RHINE/
βββ code
β βββ config
β β βββ Config.pyοΌconfigs for model.
β β βββ_init_.py
β βββ evaluation.py: evaluate the performance of learned embeddings w.r.t clustering and classification
β βββ models
β β βββ _init_.py
β β βββ Model.py: the super model with some functions
β β βββ RHINE.py: our model
β βββ preData
β β βββ dblpDataHelper.py: data preparation for our mode
β βββ release
β β βββ Sample_ARs.so: sampling with dll
β β βββ Sample_IRs.so
β βββ trainRHINE.py: train model
βββ data
β βββ dblp
β βββ node2id.txt: the first line is the number of nodes, (node_type+node_name, node_id)
β βββ paper_label.txt: (node_name, label)
β βββ relation2id.txt: the first line is the number of relations, (relation_name, relation_id)
β βββ train2id_apc.txt: (node1_id, node2_id, relation_id, weight)
β βββ train2id_pc.txt
β βββ train2id_ap.txt
β βββ train2id_pt.txt
β βββ train2id_apt.txt
β βββ train2id_ARs.txt: the first line is the number of ARs triples, (node1_id, node2_id, relation_id, weight)
β βββ train2id_IRs.txt
βββ README.md
βββ res
βββ dblp
βββ embedding.vec.ap_pt_apt+pc_apc.json: the learned embeddings
@inproceedings{Yuanfu2019RHINE,
title={Relation Structure-Aware Heterogeneous Information Network Embedding},
author={Yuanfu Lu, Chuan Shi, Linmei Hu, Zhiyuan Liu.}
booktitle={Proceedings of AAAI},
year={2019}
}