Fashion Trend Analysis & Recommendation System

Abstract

In order to ease the issue of information overload, which has become a potential concern for many Internet users, it is necessary to filter, prioritize, and efficiently distribute pertinent information on the Internet, where the quantity of options is overwhelming. One of the newest technological developments, big data has the potential to drastically alter how companies analyze and turn consumer behavior into insightful knowledge. Decision trees are also effective tools for data analysis. In order to give users individualized content and services, recommender systems scan through vast amounts of dynamically created data. Fashion recommendation systems are advanced technological solutions designed to provide personalized clothing suggestions by leveraging artificial intelligence, machine learning, and deep learning techniques. This advanced system aims to simplify fashion decision-making by offering intelligent, context-aware recommendations tailored to individual user preferences. The primary objective is to help users find the most suitable and complementary clothing items based on their existing wardrobe, personal preferences, and specific occasion requirements.