Semi-supervised Text Classification via Tensor Embedding

Method

load_data.py loads raw text as a N by D index matrix
doc2vec.py calculates tensor embeddings for each sentence
label_progagation.py calculates labels with label propagation
fabp.py calculates labels by FaBP

How to use

A complete working pipeline is shown in example.sh

Note

tensor_toolbox has its own license

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