A Literature Survey of Recent Advances in Chatbots
arXiv:2201.06657 · doi:10.3390/info13010041
Abstract
Chatbots are intelligent conversational computer systems designed to mimic human conversation to enable automated online guidance and support. The increased benefits of chatbots led to their wide adoption by many industries in order to provide virtual assistance to customers. Chatbots utilise methods and algorithms from two Artificial Intelligence domains: Natural Language Processing and Machine Learning. However, there are many challenges and limitations in their application. In this survey we review recent advances on chatbots, where Artificial Intelligence and Natural Language processing are used. We highlight the main challenges and limitations of current work and make recommendations for future research investigation.
References in corpus (6)
- Sequence to Sequence Learning with Neural Networks
- DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset
- Chameleons in imagined conversations: A new approach to understanding coordination of linguistic style in dialogs
- The Study of the Application of a Keywords-based Chatbot System on the Teaching of Foreign Languages
- Seq2Seq AI Chatbot with Attention Mechanism
- Exploring Context-Aware Conversational Agents in Software Development
Cited by in corpus (4)
- Deceptive AI Ecosystems: The Case of ChatGPT
- Beyond Traditional Teaching: The Potential of Large Language Models and Chatbots in Graduate Engineering Education
- Computational Argumentation-based Chatbots: a Survey
- Cases of EFL Secondary Students' Prompt Engineering Pathways to Complete a Writing Task with ChatGPT