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Coupled Multi-Layer Attentions for Co-Extraction of Aspect and Opinion Terms

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Coupled-Multi-layer-Attentions

Coupled Multi-Layer Attentions for Co-Extraction of Aspect and Opinion Terms

README

This is an instruction file for successfully running the CMLA model of the paper "Coupled Multi-Layer Attentions for Co-Extraction of Aspect and Opinion Terms" published in AAAI 2017: http://www.aaai.org/Conferences/AAAI/2017/PreliminaryPapers/15-Wang-W-14441.pdf


This code makes use of theano for the implementation of GRU.


Please follow these steps to run the model:

  1. Upload your sentence file and label file in util/data_semEval/

  2. Under the folder 'util', run $ python 10seqLabel.py to generate structured input data.

  3. Under the folder 'util', run $ python 20word_embedding.py to generate pre-trained word embeddings

  4. Under the main folder, run $ python train_GRU_dropout_attention.py to train a model as well as the evaluation.


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Coupled Multi-Layer Attentions for Co-Extraction of Aspect and Opinion Terms


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