AHCI RESEARCH GROUP

Publications

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

OUR RESEARCH

Scientific Publications

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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}

}

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}

}