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Project

Context-Aware Fashion Recommendations through Image Processing and Conversational Language Technology.

In an era of fast-changing trends, people struggle to create a wardrobe that fits their lifestyle and needs. With a lot of choices, it takes time and effort to find out what clothes to wear and, consequently, what clothes to buy or throw away. Professional stylists can offer support in tackling this challenge, but their services are not affordable for most customers. In addition, many existing mobile applications, which are affordable, rely on human efforts to construct such a wardrobe. Recommendation systems can perfectly fill this market niche; however, such systems usually are not able to explain their recommendations. Users want to know why the provided recommendation is given. Hence, explainable recommendations are highly demanded by users, because explainability improves the transparency, persuasiveness, effectiveness, trustworthiness, and satisfaction of recommendations for users. In this project, we aim to develop a context-aware, multi-lingual, and multi-modal recommendation system for fashion compatibility of clothes enhanced with explanation functionality. This recommendation system will be the core of a mobile application complemented by a live chat interaction with customers via a built-in chatbot, which will provide daily fashion advice based on the customers' current wardrobe, weather, and schedule. In the follow-up project, we aim to develop the proposed mobile application to deliver the technology to the b2c market. Next on, we will launch a spin-off company to constantly improve our recommendation system and implement new features in our application.
Date:1 May 2022 →  30 Sep 2023
Keywords:FASHION, ARTIFICIAL INTELLIGENCE (AI)
Disciplines:Computer vision, Information retrieval and web search, Computational linguistics