NLP is Not enough -- Contextualization of User Input in Chatbots
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.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Supporting Student Decisions on Learning Recommendations: An LLM-Based Chatbot with Knowledge Graph Contextualization for Conversational Explainability and Mentoring
Student commitment towards a learning recommendation is not separable from their understanding of the reasons it was recommended to them; and their ability to modify it based on that understanding. Among explainability a…
ChatbotCDConv: A Benchmark for Contradiction Detection in Chinese Conversations
Dialogue contradiction is a critical issue in open-domain dialogue systems. The contextualization nature of conversations makes dialogue contradiction detection rather challenging. In this work, we propose a benchmark fo…
SentenceConversational agents for learning foreign languages -- a survey
Conversational practice, while crucial for all language learners, can be challenging to get enough of and very expensive. Chatbots are computer programs developed to engage in conversations with humans. They are designed…
SurveyIf I Hear You Correctly: Building and Evaluating Interview Chatbots with Active Listening Skills
Interview chatbots engage users in a text-based conversation to draw out their views and opinions. It is, however, challenging to build effective interview chatbots that can handle user free-text responses to open-ended …
ChatbotPersonalized to Persuade: The Effects of Contextualization and Warmth on Trust and Reliance in Conversational AI
Artificial Intelligence (AI) agents personalize their responses by tailoring explanations to users' backgrounds, interests, and prior interactions, referred to as contextualization. Personalization has been identified as…