Building an Offline Rule-Based Chatbot

Leveraging a Language Model (LLM) architecture, the chatbot utilizes predefined rules for efficient user interaction. Key components include natural language understanding, dialogue management, and response generation. Challenges such as rule creation and handling ambiguous queries are addressed, alongside strategies for performance optimization. Experimental evaluation demonstrates the chatbot’s effectiveness in providing accurate responses across various scenarios. This research significantly contributes to offline chatbot technology, presenting a viable solution for deploying intelligent systems in resource constrained environments.

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Publication Details

Published
2024-11-23
DOI
https://doi.org/10.59544/wccl6338/icrcct24p85
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Building an Offline Rule-Based Chatbot

J A Smitha, B. Shadaksharappa, Rahul Raj, Pramatha P Yaji
AI in Service Interactions
article

Building an Offline Rule-Based Chatbot

J A Smitha, B. Shadaksharappa, Rahul Raj, Pramatha P Yaji
article en

Abstract

Leveraging a Language Model (LLM) architecture, the chatbot utilizes predefined rules for efficient user interaction. Key components include natural language understanding, dialogue management, and response generation. Challenges such as rule creation and handling ambiguous queries are addressed, alongside strategies for performance optimization. Experimental evaluation demonstrates the chatbot’s effectiveness in providing accurate responses across various scenarios. This research significantly contributes to offline chatbot technology, presenting a viable solution for deploying intelligent systems in resource constrained environments.

Openalex Percentile: Top 80%
AI in Service Interactions
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Building an Offline Rule-Based Chatbot — J A Smitha, B. Shadaksharappa, et al. · (2024) | TGRS Research Map | TGRS