This code implements NNQLM2 in the paper: End-to-End Quantum-like Language Models with Application to Question Answering. AAAI2018

DEPENDENCIES

• python 2.7+
• numpy
• theano
• scikit-learn (sklearn)
• ConfigParser
• cPickle
• pandas

Python packages can be easily installed using the standard tool: pip install

RUN

You can run this model by:

$ python run.py

This model is for trecqa and wikiqa. The default is for trecqa, and if you want to run this model on wikiqa, you can:

$ python run.py wiki

You can use other qa dataset. Please put your dataset on dir dataset, and preprocess your data according to trecqa.

REFERENCES

Aliaksei Severyn and Alessandro Moschitti. Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks. SIGIR, 2015.

Sordoni A, Nie J Y, Bengio Y. Modeling term dependencies with quantum language models for IR. SIGIR, 2013.

Kim Y. Convolutional Neural Networks for Sentence Classification. Eprint Arxiv, 2014.