# Chatbot System Architecture

arXiv: https://arxiv.org/abs/2201.06348 · HTML: https://mlsanity.com/paper/2201.06348/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 18 references that are in the map.
- First posted on arXiv 17 Jan 2022.

## Builds on (most cited first, 5 of 5)

- [A Neural Network Approach to Context-Sensitive Generation of Conversational Responses](https://mlsanity.com/paper/1506.06714/) (2015)
- [From Eliza to XiaoIce: Challenges and Opportunities with Social Chatbots](https://mlsanity.com/paper/1801.01957/) (2018)
- [Conversational AI: The Science Behind the Alexa Prize](https://mlsanity.com/paper/1801.03604/) (2018)
- [Contextual Topic Modeling For Dialog Systems](https://mlsanity.com/paper/1810.08135/) (2018)
- [RubyStar: A Non-Task-Oriented Mixture Model Dialog System](https://mlsanity.com/paper/1711.02781/) (2017)

## Abstract (arXiv)

The conversational agents is one of the most interested topics in computer science field in the recent decade. Which can be composite from more than one subject in this field, which you need to apply Natural Language Processing Concepts and some Artificial Intelligence Techniques such as Deep Learning methods to make decision about how should be the response. This paper is dedicated to discuss the system architecture for the conversational agent and explain each component in details.