DCoM

Deep Column Mapper is a generalized deep learning framework which classifies the type of a column given its values. Under this framework there are several models at work. This repository allows to train, finetune and predict with a DCoM model. The theoretical details of DCoM academic paper can be found here.

Data

Sample data has been provided in the data folder. The sample data is split in train, valid and test. Each CSV contains two columns, type of the column and column values. To get the access of the data contact the authors of Sherlock: A Deep Learning Approach to Semantic Data Type Detection.

Model Training

Model training is very straightforward. Change the parameters in config.py and run in the terminal,

pip install -r requirements.txt
python train.py

Model Finetuning

Set the path of a pretrained model and metadata in INITIAL_MODEL_WEIGHT_PATH and INITIAL_METADATA_PATH respectively in config.py to finetune the model from the given checkpoint.

Model Predictions

Sample prediction on test data is shown in notebook.ipynb.

Results

Using a novel data preparation technique and NLP models, DCoM outperforms other works in this domain. The table compares the performace of DCoM with others.

Method	Engineered Features	k	F1 Score	Runtime (s)	Size (MB)
DCoM-Single-LSTM	Yes	1	0.895	0.019	112.1
DCoM-Single-LSTM	Yes	10	0.898	0.152	112.1
DCoM-Single-LSTM	No	1	0.871	0.018	97.8
DCoM-Single-LSTM	No	10	0.877	0.141	97.8
DCoM-Multi-LSTM	Yes	1	0.878	0.046	4.7
DCoM-Multi-LSTM	Yes	10	0.881	0.416	4.7
DCoM-Multi-LSTM	No	1	0.869	0.044	4.6
DCoM-Multi-LSTM	No	10	0.871	0.401	4.6
DCoM-Single-DistilBERT	Yes	1	0.922	0.162	268.2
DCoM-Single-DistilBERT	Yes	10	0.925	1.552	268.2
DCoM-Single-DistilBERT	No	1	0.901	0.158	202.3
DCoM-Single-DistilBERT	No	10	0.904	1.492	202.3
DCoM-Single-Electra	Yes	1	0.907	0.093	53.1
DCoM-Single-Electra	Yes	10	0.909	0.894	53.1
DCoM-Single-Electra	No	1	0.890	0.092	45.7
DCoM-Single-Electra	No	10	0.892	0.887	45.7
Sherlock	-	-	0.890	0.42	6.2

Citation

This paper is submitted for publication. If you are using this model then please use the below BibTeX to cite for now.

@ARTICLE{2021arXiv210612871M,
       author = {{Maji}, Subhadip and {Sourav Rout}, Swapna and {Choudhary}, Sudeep},
        title = "{DCoM: A Deep Column Mapper for Semantic Data Type Detection}",
      journal = {arXiv e-prints},
     keywords = {Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Statistics - Machine Learning},
         year = 2021,
        month = jun,
          eid = {arXiv:2106.12871},
        pages = {arXiv:2106.12871},
archivePrefix = {arXiv},
       eprint = {2106.12871},
 primaryClass = {cs.LG},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2021arXiv210612871M},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

More Information

For any clarification feel free to raise an issue. Additionally you can reach us at subhadipmaji.jumech@gmail.com