Giancarlo Frison Signals from the Noise

Automated Question Answering using Semantic Networks

I worked recently in a small prototype that combines NLP analysis and semantic datasources for answering simple generic questions, by learning how to get the informations given a fairly small amount of question/answer pairs.

Conversational interactions represents the core of any modern Chatbot and the ability to manage utterances and conversations is the strongest indicator of user’s satisfaction. A natural and spontaneous QA dialogue, as every Chatbot would aim to engage, will attempt to solve 3 fundamental issues:

  1. Classify utterances and extract dependencies between words.
  2. Integrate source of knowledge.
  3. Infer transitive semantics (e.g., reconstructing what it is implied but not written).

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