AlgMap

The source code and data used in the KDD'2019 paper Mining Algorithm Roadmap in Scientific Publications. A corresponding online demo can be found at http://fts.cs.ucsb.edu/roadmap.

Requirements

Python 3.6
pytorch 1.0
sqlite3
pdffigures, https://github.com/allenai/pdffigures
Other python requirements, pip install -r requirements.txt

Preprocessing

Codes in preprocess folder prepare data needed for constructing Algorithm Roadmap. In the experiment, datasets are NIPS, ACL and VLDB.

cd preprocess/

Convert Pdf To Text

Set the correct data path and use the following script to batchly execute pdftotext.

python convert2txt_multithread.py ${dataset}

Clean Text Corpus

Clean the converted txt files, remove non-ascii characters etc.

python textcleaner.py ${dataset}

Extract Table Json Files From Pdf

Extract tables from pdf files for later weak supervision extraction, relying on pdffigures.

python pdf2figure.py tablejson ${dataset}

Create Database

Use sqlite3 database to store the corpus for later instance collection.

python create_db.py ${dataset}
python concat_docs_in_one_file.py ${dataset}

Pre-train Word Embedding

python pretrain_wordvec.py ${dataset}

Build Vocabulary

python build_vocab.py ${dataset}

Parse Table Json Files

Parse table json files to extract weak supervision.

python parse_table.py ${dataset}

Save Co-occurred Acronyms

Save co-occured acronyms which are baseline methods used in the experiment.

python save_coocurred_abbvs.py ${dataset}

Prepare Final Data

Cut off long paragraphs and long sentences, do labelling, padding, and data splitting for final relation extraction. Prepare instances for acronym pairs, feature_type standard or paragraph denote single-sentence or cross-sentence instances.

python parse_abbv_in_sents.py ${dataset}
python prepare_final_data.py ${dataset} ${feature_type}

Pre-processed Dataset

Pre-processed NIPS, ACL, VLDB datasets before running prepare_final_data.py.

https://drive.google.com/open?id=1R00G5xP141SO5oCt9zL8-COsX5G2H8dy

Train And Test

Train Model

Train our CANTOR relation extraction model.

python train_cantor.py ${dataset} cantor ${feature_type}

Evaluate Model

Evaluate model and save predictions.

python model_eval.py ${dataset} cantor ${feature_type}

Construct Algorithm Roadmap

Construct algorithm roadmap for a query.

python construct_roadmap.py 

References

If you found the repository useful, please cite the following:

H. Zha, W. Chen, K. L, X. Yan, Mining Algorithm Roadmap in Scientific Publications

@inproceedings{zha2019mining,
  title={Mining Algorithm Roadmap in Scientific Publications},
  author={Hanwen Zha, Wenhu Chen, Keqian Li and Xifeng Yan},
  booktitle={Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining., {KDD}},
  year={2019}
}