AHCI RESEARCH GROUP

Publications

Papers published in international journals,
proceedings of conferences, workshops and books.

OUR RESEARCH

Scientific Publications

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2025

Saengthongkam, S.; Ali, S.; Chokphantavee, S.; Chokphantavee, S.; Noisri, S.; Vanichchanunt, P.; Butcharoen, S.; Boontevee, S.; Phanomchoeng, G.; Deepaisarn, S.; Wuttisittikulkij, L.

AI-Powered Virtual Assistants in the Metaverse: Leveraging Retrieval-Augmented Generation for Smarter Interactions Proceedings Article

In: Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 9798331522230 (ISBN).

Abstract | Links | BibTeX | Tags: AI, Artificial intelligence, chatbot, Chatbots, Cosine similarity, Intelligent Agents, Load testing, Metaverse, Metaverses, On the spots, Performance, Search engines, Similarity scores, user experience, User query, User support, Users' satisfactions, Virtual assistants, Virtual Reality

@inproceedings{saengthongkam_ai-powered_2025,

title = {AI-Powered Virtual Assistants in the Metaverse: Leveraging Retrieval-Augmented Generation for Smarter Interactions},

author = {S. Saengthongkam and S. Ali and S. Chokphantavee and S. Chokphantavee and S. Noisri and P. Vanichchanunt and S. Butcharoen and S. Boontevee and G. Phanomchoeng and S. Deepaisarn and L. Wuttisittikulkij},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105014379689&doi=10.1109%2FECTI-CON64996.2025.11101141&partnerID=40&md5=3f81fb234377399184ad031c8aa65333},

doi = {10.1109/ECTI-CON64996.2025.11101141},

isbn = {9798331522230 (ISBN)},

year  = {2025},

date = {2025-01-01},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {The metaverse has evolved at an unprecedented pace, creating new demands for on the spot user support and more engaging digital encounters. This paper describes a chatbot system built for the NT metaverse that combines retrieval-based search with advanced generative AI methods to provide accurate, context-driven responses. At the core of our approach is Retrieval Augmented Generation (RAG), which adeptly interprets diverse user queries while sustaining high performance under concurrent usage, as evidenced by a cosine similarity score of 0.79. In addition to maintaining efficiency during load testing, the system manages compound queries with ease, enhancing user satisfaction in complex virtual environments. Although these results are promising, future upgrades such as integrating voice-based interactions, multilingual support, and adaptive learning could further expand the chatbot's utility. Overall, this study demonstrates the tangible benefits of AI-driven conversational agents in digital realms, laying the groundwork for richer, more intelligent user experiences in emerging metaverse platforms. © 2025 Elsevier B.V., All rights reserved.},

keywords = {AI, Artificial intelligence, chatbot, Chatbots, Cosine similarity, Intelligent Agents, Load testing, Metaverse, Metaverses, On the spots, Performance, Search engines, Similarity scores, user experience, User query, User support, Users' satisfactions, Virtual assistants, Virtual Reality},

pubstate = {published},

tppubtype = {inproceedings}

}