Subword Language Model for Query Auto-Completion

This is the official github repository for Subword Language Model for Query Auto-Completion (EMNLP-IJCNLP 2019).

Dependencies

• Python 3
• PyTorch
• SentencePiece

Preparing Data

• Dowload original AOL query log dataset: ./get_data.sh. This files will be saved in data/aol/org directory.
• Split this data into {train, valid, test}.{query, uid, time}.txt by giving name tag for the split and specifying time interval of each split. It will be generated in the data/aol/<tag> directory. Or, you can just run split.sh to use a pre-determined partition setting.

  python split.py --tag full  --train_start "2006-03-01 00:00:00" --train_end "2006-05-18 00:00:00" \
                              --valid_start "2006-05-18 00:00:00" --valid_end "2006-05-25 00:00:00" \
                              --test_start  "2006-05-25 00:00:00" --test_end  "2006-06-01 00:00:00"
  

• Train SentencePiece models (char, bpe, and unigram): ./train_spms.sh. You may change the subword vocabulary size (default: 256).

Training a language model

python train.py \
    --data_dir data/aol/full \
    --spm <spm> \               # char, bpe/<vocab-size>, or unigram/<vocab-size> 
    --sample -1 0.2 \           # if spm is ungiram
    --ninp 100 \
    --nhid 600 \
    --nlayers 1 \
    --max_seq_len 40

Generating completions using a trained language model

python generate.py \
    --gen_bsz 1 \
    --beam_size 30 \
    --branching_factor 30 \
    --retrace <R> \             # for the retrace algorithm
    --nbest <n> \               # for the n-best decoding
    --do_merge \                # for marginalization

Citation

If you find this work useful, please cite:

@article{kim2019subword,
  title={Subword Language Model for Query Auto-Completion},
  author={Kim, Gyuwan},
  journal={arXiv preprint arXiv:1909.00599},
  year={2019}
}

Contact Information

Please feel free to contact Gyuwan Kim ([email protected]) if there is any question.

License

MIT License

Copyright (c) 2019-present NAVER Corp.

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