Research Article
AI-Driven Personalized Outfit Recommendation with NLP and GAN Enhanced Chatbot
@INPROCEEDINGS{10.4108/eai.28-4-2025.2357796, author={Deekshitha C and Srinivas I and Smitheash AR and P Ranjana}, title={AI-Driven Personalized Outfit Recommendation with NLP and GAN Enhanced Chatbot}, proceedings={Proceedings of the 4th International Conference on Information Technology, Civil Innovation, Science, and Management, ICITSM 2025, 28-29 April 2025, Tiruchengode, Tamil Nadu, India, Part I}, publisher={EAI}, proceedings_a={ICITSM PART I}, year={2025}, month={10}, keywords={ai fashion assistant personalized recommendations machine learning natural language processing fashion recommender system body measurements stable diffusion custom design generation computer vision user preferences}, doi={10.4108/eai.28-4-2025.2357796} }- Deekshitha C
Srinivas I
Smitheash AR
P Ranjana
Year: 2025
AI-Driven Personalized Outfit Recommendation with NLP and GAN Enhanced Chatbot
ICITSM PART I
EAI
DOI: 10.4108/eai.28-4-2025.2357796
Abstract
A new AI-powered fashion assistant which employs machine learning strategies operates as our core presentation to elevate the online shopping operations. The system uses fashion item recommendations since it integrates both user preferences alongside body measurements and visual search functions. Natural language processing (NLP) performs with image generation models like Stable Diffusion to generate individual fashion designs through the assistant. Through our method we generate specific fashion product recommendations that know about user demographics along with personal style characteristics and their actual dimensions. The recommender system delivers recommendations through a content-based filtering method that focuses on precision and satisfaction among users when matching them with clothing products. The combination of features like deep learning along with computer vision permits us to establish an advanced responsive fashion recommendation platform. The obtained results show how AI-motorized instruments have the capability to revolutionize the fashion sector by developing shopping encounters which better understand individual preferences.
