Apparel Recommendation System using Content-Based Filtering

Nowadays, people are constantly moving towards various fashion products as a result the e-commerce market for garments is growing rapidly. Online stores must update their features according to user requirements and preferences. However, there too many options users select from these online which may leave them in dilemma identify correct outfit, save time, increase sales, efficient recommendation systems becoming necessity retailers. In this paper, we proposed an Apparel Recommendation System that generates recommendations based on input. We used real-world data set taken giant Amazon using Amazon’s Product Advertising API. aim use keywords like brand, color, size, etc., recommend. Data exploration get detailed information about our dataset, Cleaning(pre-processing) remove invalid sections, Model selection (We have compared different feature extraction techniques bag of words, TF-IDF, word2vec model) find out Deployment model could facilitate system simplify task apparel system. The accuracy identified response time content matching.