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This is a sample implementation of "Arbitrary-Order Proximity Preserved Network Embedding"(KDD 2018).
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AROPE.m
BlogCatalog.csv
Eigen_Reweighting.m
Eigen_TopL.m
KDD18AROPE.pdf
Precision_Np.m
README.md
SampleRun.m
Shift_Embedding.m

README.md

AROPE

This is a sample implementation of "Arbitrary-Order Proximity Preserved Network Embedding"(KDD 2018).

Requirements

MATLAB R2017a

Usage

Main Function

[U_output, V_output] = AROPE(A,d,order,weights)
Input:
    A: sparse adjacency matrix or its variations, must be symmetric
    d: dimensionality 
    order: 1 x r vector, order of the proximity
    weights: 1 x r cell, each containing the weights for one high-order proximity
Output:
    U_output/V_output: 1 x r cell, each containing one content/context embedding vectors 

Example Usage

See SampleRun.m for a sample run of network reconstruction on BlogCatalog dataset

Cite

If you find this code useful, please cite our paper:

@inproceedings{zhang2018arbitrary,
  title={Arbitrary-Order Proximity Preserved Network Embedding},
  author={Zhang, Ziwei and Cui, Peng and Wang, Xiao and Pei, Jian and Yao, Xuanrong and Zhu, Wenwu},
  booktitle={Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
  year={2018},
  organization={ACM}
}
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