AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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Here you can find the complete list of our publications.
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You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2025
Lakehal, A.; Alti, A.; Annane, B.
CORES: Context-Aware Emotion-Driven Recommendation System-Based LLM to Improve Virtual Shopping Experiences Journal Article
In: Future Internet, vol. 17, no. 2, 2025, ISSN: 19995903 (ISSN).
Abstract | Links | BibTeX | Tags: Context, Context-Aware, Customisation, Decisions makings, E- commerces, e-commerce, Emotion, emotions, Language Model, Large language model, LLM, Recommendation, Virtual environments, Virtual Reality, Virtual shopping
@article{lakehal_cores_2025,
title = {CORES: Context-Aware Emotion-Driven Recommendation System-Based LLM to Improve Virtual Shopping Experiences},
author = {A. Lakehal and A. Alti and B. Annane},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85218626299&doi=10.3390%2ffi17020094&partnerID=40&md5=a0f68e273de08b2c33d03da4cb6c19bb},
doi = {10.3390/fi17020094},
issn = {19995903 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Future Internet},
volume = {17},
number = {2},
abstract = {In today’s business landscape, artificial intelligence (AI) plays a pivotal role in shopping processes and customization. As the demand for customization grows, virtual reality (VR) emerges as an innovative solution to improve users’ perception and decision making in virtual shopping experiences (VSEs). Despite its potential, limited research has explored the integration of contextual information and emotions in VR to deliver effective product recommendations. This paper presents CORES (context-aware emotion-driven recommendation system), a novel approach designed to enrich users’ experiences and to support decision making in VR. CORES combines advanced large language models (LLMs) and embedding-based context-aware recommendation strategies to provide customized products. Therefore, emotions are collected from social platforms, and relevant contextual information is matched to enable effective recommendation. Additionally, CORES leverages transformers and retrieval-augmented generation (RAG) capabilities to explain recommended items, facilitate VR visualization, and generate insights using various prompt templates. CORES is applied to a VR shop of different items. An empirical study validates the efficiency and accuracy of this approach, achieving a significant average accuracy of 97% and an acceptable response time of 0.3267s in dynamic shopping scenarios. © 2025 by the authors.},
keywords = {Context, Context-Aware, Customisation, Decisions makings, E- commerces, e-commerce, Emotion, emotions, Language Model, Large language model, LLM, Recommendation, Virtual environments, Virtual Reality, Virtual shopping},
pubstate = {published},
tppubtype = {article}
}
In today’s business landscape, artificial intelligence (AI) plays a pivotal role in shopping processes and customization. As the demand for customization grows, virtual reality (VR) emerges as an innovative solution to improve users’ perception and decision making in virtual shopping experiences (VSEs). Despite its potential, limited research has explored the integration of contextual information and emotions in VR to deliver effective product recommendations. This paper presents CORES (context-aware emotion-driven recommendation system), a novel approach designed to enrich users’ experiences and to support decision making in VR. CORES combines advanced large language models (LLMs) and embedding-based context-aware recommendation strategies to provide customized products. Therefore, emotions are collected from social platforms, and relevant contextual information is matched to enable effective recommendation. Additionally, CORES leverages transformers and retrieval-augmented generation (RAG) capabilities to explain recommended items, facilitate VR visualization, and generate insights using various prompt templates. CORES is applied to a VR shop of different items. An empirical study validates the efficiency and accuracy of this approach, achieving a significant average accuracy of 97% and an acceptable response time of 0.3267s in dynamic shopping scenarios. © 2025 by the authors.
2024
Wong, A.; Zhao, Y.; Baghaei, N.
Effects of Customizable Intelligent VR Shopping Assistant on Shopping for Stress Relief Proceedings Article
In: U., Eck; M., Sra; J., Stefanucci; M., Sugimoto; M., Tatzgern; I., Williams (Ed.): Proc. - IEEE Int. Symp. Mixed Augment. Real. Adjunct, ISMAR-Adjunct, pp. 304–308, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-833150691-9 (ISBN).
Abstract | Links | BibTeX | Tags: Customisation, Customizable, generative artificial intelligence, Head-mounted-displays, Helmet mounted displays, Immersive, Mental health, mHealth, Realistic rendering, stress, Stress relief, Users' experiences, Virtual environments, Virtual Reality, Virtual shopping, Virtual shopping assistant
@inproceedings{wong_effects_2024,
title = {Effects of Customizable Intelligent VR Shopping Assistant on Shopping for Stress Relief},
author = {A. Wong and Y. Zhao and N. Baghaei},
editor = {Eck U. and Sra M. and Stefanucci J. and Sugimoto M. and Tatzgern M. and Williams I.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214427097&doi=10.1109%2fISMAR-Adjunct64951.2024.00069&partnerID=40&md5=1530bc0a2139fb33b1a2917c3eb31296},
doi = {10.1109/ISMAR-Adjunct64951.2024.00069},
isbn = {979-833150691-9 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Proc. - IEEE Int. Symp. Mixed Augment. Real. Adjunct, ISMAR-Adjunct},
pages = {304–308},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Shopping has long since been a method of distraction and relieving stress. Virtual Reality (VR) effectively simulates immersive experiences, including shopping through head-mounted displays (HMD), which create an environment through realistic renderings and sounds. Current studies in VR have shown that assistants can support users by reducing stress, indicating their ability to improve mental health within VR. Customization and personalization have also been used to enhance the user experience with users preferring the tailored experience and leading to a greater sense of immersion. There is a gap in knowledge on the effects of customization on a VR assistant's ability to reduce stress within the VR retailing space. This research aims to identify relationships between customization and shopping assistants within VR to better understand its effects on the user experience. Understanding this will help the development of VR assistants for mental health and consumer-ready VR shopping experiences. © 2024 IEEE.},
keywords = {Customisation, Customizable, generative artificial intelligence, Head-mounted-displays, Helmet mounted displays, Immersive, Mental health, mHealth, Realistic rendering, stress, Stress relief, Users' experiences, Virtual environments, Virtual Reality, Virtual shopping, Virtual shopping assistant},
pubstate = {published},
tppubtype = {inproceedings}
}
Shopping has long since been a method of distraction and relieving stress. Virtual Reality (VR) effectively simulates immersive experiences, including shopping through head-mounted displays (HMD), which create an environment through realistic renderings and sounds. Current studies in VR have shown that assistants can support users by reducing stress, indicating their ability to improve mental health within VR. Customization and personalization have also been used to enhance the user experience with users preferring the tailored experience and leading to a greater sense of immersion. There is a gap in knowledge on the effects of customization on a VR assistant's ability to reduce stress within the VR retailing space. This research aims to identify relationships between customization and shopping assistants within VR to better understand its effects on the user experience. Understanding this will help the development of VR assistants for mental health and consumer-ready VR shopping experiences. © 2024 IEEE.
2023
Le, M. -H.; Chu, C. -B.; Le, K. -D.; Nguyen, T. V.; Tran, M. -T.; Le, T. -N.
VIDES: Virtual Interior Design via Natural Language and Visual Guidance Proceedings Article
In: G., Bruder; A.H., Olivier; A., Cunningham; E.Y., Peng; J., Grubert; I., Williams (Ed.): Proc. - IEEE Int. Symp. Mixed Augment. Real. Adjunct, ISMAR-Adjunct, pp. 689–694, Institute of Electrical and Electronics Engineers Inc., 2023, ISBN: 979-835032891-2 (ISBN).
Abstract | Links | BibTeX | Tags: Architectural design, Customisation, Cutting edge technology, Design concept, Design systems, Image editing, Image generation, Image generations, Indoor space, Interior Design, Interior designs, Interiors (building), Natural languages, Virtual Reality, Visual guidance, Visual languages
@inproceedings{le_vides_2023,
title = {VIDES: Virtual Interior Design via Natural Language and Visual Guidance},
author = {M. -H. Le and C. -B. Chu and K. -D. Le and T. V. Nguyen and M. -T. Tran and T. -N. Le},
editor = {Bruder G. and Olivier A.H. and Cunningham A. and Peng E.Y. and Grubert J. and Williams I.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180376943&doi=10.1109%2fISMAR-Adjunct60411.2023.00148&partnerID=40&md5=5ce45d9e97fc5a9fdc31eb7514b3def3},
doi = {10.1109/ISMAR-Adjunct60411.2023.00148},
isbn = {979-835032891-2 (ISBN)},
year = {2023},
date = {2023-01-01},
booktitle = {Proc. - IEEE Int. Symp. Mixed Augment. Real. Adjunct, ISMAR-Adjunct},
pages = {689–694},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Interior design is crucial in creating aesthetically pleasing and functional indoor spaces. However, developing and editing interior design concepts requires significant time and expertise. We propose Virtual Interior DESign (VIDES) system in response to this challenge. Leveraging cutting-edge technology in generative AI, our system can assist users in generating and editing indoor scene concepts quickly, given user text description and visual guidance. Using both visual guidance and language as the conditional inputs significantly enhances the accuracy and coherence of the generated scenes, resulting in visually appealing designs. Through extensive experimentation, we demonstrate the effectiveness of VIDES in developing new indoor concepts, changing indoor styles, and replacing and removing interior objects. The system successfully captures the essence of users' descriptions while providing flexibility for customization. Consequently, this system can potentially reduce the entry barrier for indoor design, making it more accessible to users with limited technical skills and reducing the time required to create high-quality images. Individuals who have a background in design can now easily communicate their ideas visually and effectively present their design concepts. © 2023 IEEE.},
keywords = {Architectural design, Customisation, Cutting edge technology, Design concept, Design systems, Image editing, Image generation, Image generations, Indoor space, Interior Design, Interior designs, Interiors (building), Natural languages, Virtual Reality, Visual guidance, Visual languages},
pubstate = {published},
tppubtype = {inproceedings}
}
Interior design is crucial in creating aesthetically pleasing and functional indoor spaces. However, developing and editing interior design concepts requires significant time and expertise. We propose Virtual Interior DESign (VIDES) system in response to this challenge. Leveraging cutting-edge technology in generative AI, our system can assist users in generating and editing indoor scene concepts quickly, given user text description and visual guidance. Using both visual guidance and language as the conditional inputs significantly enhances the accuracy and coherence of the generated scenes, resulting in visually appealing designs. Through extensive experimentation, we demonstrate the effectiveness of VIDES in developing new indoor concepts, changing indoor styles, and replacing and removing interior objects. The system successfully captures the essence of users' descriptions while providing flexibility for customization. Consequently, this system can potentially reduce the entry barrier for indoor design, making it more accessible to users with limited technical skills and reducing the time required to create high-quality images. Individuals who have a background in design can now easily communicate their ideas visually and effectively present their design concepts. © 2023 IEEE.