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Update README.md
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Take DBLP dataset as an example:
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python train.py --dataset='dblp'
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# Guide on Generation of Semantic Embeddings
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# FAQ
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## Code of preprocessing data?
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The data is originally preprocessed by GTN project (https://github.com/seongjunyun/Graph_Transformer_Networks).
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## How to generate semantic embeddings?
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The semantic embeddings, i.e. $\mathcal{Z}$ in the paper, are generated by metapath2vec algorithm. Users may refer to https://github.com/dmlc/dgl/tree/master/examples/pytorch/metapath2vec for an implementation.
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