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EMNLP 2018: AD3: Attentive Deep Document Dater :: Swayambhu Nath Ray, Shib Sankar Dasgupta, Partha Talukdar

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AD3

AD3: Attentive Deep Document Dater

Source code and dataset for EMNLP 2018 paper: AD3: Attentive Deep Document Dater.

Overview of AD3 (proposed method), an attention-based neural document dating system which utilizes both context and temporal information in documents in a flexible and principled manner. Please refer paper for more details.

Dependencies

  • Compatible with TensorFlow 1.x and Python 3.x.
  • Dependencies can be installed using requirements.txt.

Dataset:

Usage:

  • After installing python dependencies from requirements.txt, execute sh setup.sh for downloading GloVe embeddings.

  • ac_gcn.py and oe_gcn.py contains TensorFlow (1.x) based implementation of AD3 (proposed method).

  • To start training:

    python ac_gcn.py -data data/nyt_processed_data.pkl -class 10 -name test_run
    python oe_gcn.py -data data/nyt_processed_data.pkl -class 10 -name test_run
    • -class denotes the number of classes in datasets, 10 for NYT and 16 for APW.
    • -name is arbitrary name for the run.

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EMNLP 2018: AD3: Attentive Deep Document Dater :: Swayambhu Nath Ray, Shib Sankar Dasgupta, Partha Talukdar

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