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I am trying to build a question answering system where I have a set of predefined questions and their answers. For any given question from the user I have to find if the similar question already exists in the predefined questions and send answers. If it doesn't exist it has to reply a generic response. Any ideas on how to implement this using NLP would be really helpful.

Thanks in advance!!

nikhil kumar koditala
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As you have already mentioned in the question, this calls for a solution that computes text similarity. In this case question-question similarity. You have got a bunch of questions and for an incoming query/question, a similarity score has to be computed with every available question in hand. From a previous answer of mine, to do simple sentence similarity,

  1. Convert the sentences into as suitable representation
  2. Compute some of distance metric between the two representations and figure out the closest match

To achieve 1, you can consider converting every word in a sentence to corresponding vectors. There are libraries/algorithms like fasttext that provide vector mapping. A vector representation of the entire sentence is obtained by taking an average over all word vectors. Use cosine similarity to compute a score between the query and each question in the available list.

scarecrow
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