NLP is Not enough -- Contextualization of User Input in Chatbots
- URL: http://arxiv.org/abs/2105.06511v1
- Date: Thu, 13 May 2021 18:57:32 GMT
- Title: NLP is Not enough -- Contextualization of User Input in Chatbots
- Authors: Nathan Dolbir, Triyasha Dastidar, and Kaushik Roy
- Abstract summary: Advanced Natural Language Processing techniques, based on deep networks, efficiently process user requests to carry out their functions.
As chatbots gain traction, their applicability in healthcare is an attractive proposition due to the reduced economic and people costs of an overburdened system.
However, healthcare bots require safe and medically accurate information capture, which deep networks aren't yet capable of due to user text and speech variations.
- Score: 4.833037692738672
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: AI chatbots have made vast strides in technology improvement in recent years
and are already operational in many industries. Advanced Natural Language
Processing techniques, based on deep networks, efficiently process user
requests to carry out their functions. As chatbots gain traction, their
applicability in healthcare is an attractive proposition due to the reduced
economic and people costs of an overburdened system. However, healthcare bots
require safe and medically accurate information capture, which deep networks
aren't yet capable of due to user text and speech variations. Knowledge in
symbolic structures is more suited for accurate reasoning but cannot handle
natural language processing directly. Thus, in this paper, we study the effects
of combining knowledge and neural representations on chatbot safety, accuracy,
and understanding.
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