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Match Zoo Adapation for CIKM AnalytiCup 2018

1. Data preparation

Originate from path CIKMAnalytiCup2018/MatchZoo/examples/toy_example/generate_classification_data.sh Status: https://github.com/NTSC-Community/awaresome-neural-models-for-semantic-match

Generate matchzoo data for ranking

cd CIKMAnalytiCup2018/MatchZoo/examples/toy_example/
python test_preparation_for_classify.py

Download embedding

wget http://nlp.stanford.edu/data/glove.6B.zip
unzip glove.6B.zip
mv glove.6B.50d.txt ../../data/toy_example/classification/

Map word embedding

python gen_w2v.py ../../data/toy_example/classification/glove.6B.50d.txt ../../data/toy_example/classification/word_dict.txt ../../data/toy_example/classification/embed_glove_d50
python norm_embed.py  ../../data/toy_example/classification/embed_glove_d50 ../../data/toy_example/classification/embed_glove_d50_norm
  • norm_embed.py can be skipped for the first phase

Run to generate binsum for aNMM

python test_binsum_generator.py 'classification'

2. Run train and predict phase

$ python matchzoo/main.py --phase train --model_file examples/toy_example/config/anmm_classify.config