Apparel Recommendation Engine Using Inverse Document Frequency and Weighted Average Word2vec

Abstract

The rapid development of e-commerce shopping marketplaces necessitates the use of recommendation engines and quick, precise, and efficient algorithms in order for the company's business models to generate a massive amount of profit. A computer vision software programme enables a computer to learn a great deal from digital images or movies. Machine learning methods are used in computer vision, and several machine learning techniques have been developed specifically for this purpose. Information retrieval is the process of extracting useful information from a dataset, and computer vision is the most commonly used tool for this purpose nowadays. This project consists of a series of modules that run sequentially to retrieve information from a marked area on a receipt. A receipt image is used as an input for the model, and the model first uses various image processing algorithms to clean the data, after which the pre-processed data is applied to machine learning algorithms to produce better results, and the result is a string of numerical digits including the decimal point. The program's accuracy is primarily determined by the image quality or pixel density, and it is necessary to ensure that an input receipt is not damaged and content is not blurred.