title: Building a closed domain QA system using LSTM
body: <p>My objective is to build a closed domain question answering system from a set of documents containing knowledge about the domain. I have gone through a bunch of research papers which implement such a system using Recurrent Neural Networks (mostly, LSTM). All these papers have training data in the Question-answer pairs format, which is not the case with my problem. Also, its not feasible to generate QA pairs from my document corpus.</p>
  
  <p>Is there any research paper or any method I can follow to achieve this?
  (Preferably using LSTM or any neural network, because they tend to give better results. If not, any other method should also do.) </p>