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EP-Bot: Empathetic Chatbot Using Auto-Growing Knowledge Graph

SoYeop Yoo, OkRan Jeong*

Gachon University, Seongnam-si, 13120, Korea

* Corresponding Author: OkRan Jeong. Email: email

Computers, Materials & Continua 2021, 67(3), 2807-2817.


People occasionally interact with each other through conversation. In particular, we communicate through dialogue and exchange emotions and information from it. Emotions are essential characteristics of natural language. Conversational artificial intelligence is an integral part of all the technologies that allow computers to communicate like humans. For a computer to interact like a human being, it must understand the emotions inherent in the conversation and generate the appropriate responses. However, existing dialogue systems focus only on improving the quality of understanding natural language or generating natural language, excluding emotions. We propose a chatbot based on emotion, which is an essential element in conversation. EP-Bot (an Empathetic PolarisX-based chatbot) is an empathetic chatbot that can better understand a person’s utterance by utilizing PolarisX, an auto-growing knowledge graph. PolarisX extracts new relationship information and expands the knowledge graph automatically. It is helpful for computers to understand a person’s common sense. The proposed EP-Bot extracts knowledge graph embedding using PolarisX and detects emotion and dialog act from the utterance. Then it generates the next utterance using the embeddings. EP-Bot could understand and create a conversation, including the person’s common sense, emotion, and intention. We verify the novelty and accuracy of EP-Bot through the experiments.


Cite This Article

S. Yoo and O. Jeong, "Ep-bot: empathetic chatbot using auto-growing knowledge graph," Computers, Materials & Continua, vol. 67, no.3, pp. 2807–2817, 2021.


cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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