title: Whoosh for Non-Boolean Search Queries
body: <p>I am building a question answering system, and to speed up the process I want an IR system to return a set of documents from a corpus likely to hold the answer to that question (and my NLP algorithm will try to figure out the answer from the full text of those).</p>
  
  <p>Since I'm using Python, Whoosh seemed like a good choice, but I'm having a difficult time searching in a method other than pure boolean queries, which don't lend themselves to question answering. I'd like something like a list of documents with high TF-IDF similarity to a string query.</p>
  
  <p>I'd like to input:</p>
  
  <blockquote>
    <p>"Who is the president of the United States?"</p>
  </blockquote>
  
  <p>and get the most similar documents, but instead I just strip out stopwords to have:</p>
  
  <blockquote>
    <p>"president OR united OR states"</p>
  </blockquote>
  
  <p>The exactness doesn't lend itself to a QA process. Can anyone point me to some methods or advanced API methods to get top documents in a non-boolean way? I'd be willing to try other libraries, but most seem  complex to interface quickly with Python, and I was hoping to have something super easy so I could move on to focus on the natural language component.</p>