HHNE
Source code for AAAI-2019 paper "Hyperbolic Heterogeneous Information Network Embedding"
The HHNE code is built upon Mikolov et al.'s word2vec.c from https://code.google.com/archive/p/word2vec/
Compile
- cmd "make" in folder HHNE/code/
- run "hhne" in folder HHNE/code/
Usage
./hhne [options]
The Options follow Mikolov et al.'s word2vec Options for training:
-train <file>
Use text data from <file> to train the model
-output <file>
Use <file> to save the resulting word vectors / word clusters
-size <int>
Set size of word vectors; default is 100
-window <int>
Set max skip length between words; default is 5
-sample <float>
Set threshold for occurrence of words. Those that appear with higher frequency in the training data
will be randomly down-sampled; default is 1e-3, useful range is (0, 1e-5)
-negative <int>
Number of negative examples; default is 5, common values are 3 - 10 (0 = not used)
-threads <int>
Use <int> threads (default 12)
-iter <int>
Run more training iterations (default 5)
-min-count <int>
This will discard words that appear less than <int> times; default is 5
-alpha <float>
Set the starting learning rate; default is 0.025 for skip-gram
-debug <int>
Set the debug mode (default = 2 = more info during training)
-save-vocab <file>
The vocabulary will be saved to <file>
-read-vocab <file>
The vocabulary will be read from <file>, not constructed from the training data
Examples:
./hhne -train random_walks.txt -output hhne.embeddings -size 2 -window 5 -negative 10 -threads 32 -iter 5 -alpha 0.025
Input:
The walks generated by meta-path guided random walks, each of which consists of different types of nodes.
Output:
The file for each node in text format (e.g., hhne.embeddings.txt)
HHNE bibtex information
@article{zhang2021embedding,
title={Embedding Heterogeneous Information Network in Hyperbolic Spaces},
author={Zhang, Yiding and Wang, Xiao and Liu, Nian and Shi, Chuan},
journal={ACM Transactions on Knowledge Discovery from Data (TKDD)},
volume={16},
number={2},
pages={1--23},
year={2021},
publisher={ACM New York, NY}
}
@inproceedings{HHNE:AAAI19,
title={Hyperbolic Heterogeneous Information Network Embedding},
author = {Wang, Xiao and Zhang, Yiding and Shi, Chuan},
booktitle = {AAAI},
year = {2019},
}