Research progress on key technologies of clothing recommendation systems
As the scale of e-commerce continues to expand,the number and variety of products are rapidly increasing,requiring customers to spend a considerable amount of time to find the products they need.This process of browsing through large amounts of irrelevant information and products undoubtedly leads consumers to be drown in an overload of information.To address this issue,recommendation systems have emerged.Recommendation systems are advanced business intelligence platforms built on massive data mining foundations,designed to provide e-commerce websites with personalized decision support and information services tailored to their customers.The emergence and development of the Internet have triggered a digital storm,gradually applying recommendation technology to various fields such as e-commerce,news delivery,social networking,and music entertainment.Clothing,as an important component of the fashion industry,benefits from the integration of the Internet and the fashion industry,bringing new possibilities for clothing design,production,and consumption.Clothing recommendation,as a significant research direction in the computer fashion field,has garnered widespread attention from fields like computer vision,multimedia,and information retrieval.Compared to traditional offline shopping,online purchase of clothing and accessories is more convenient.A typical recommendation system predicts user interest in a particular item based on given information about the product and the user,as well as interaction history,thereby providing personalized products or services to the user.Clothing recommendation can be seen as a specific application of recommendation systems in the field of e-commerce,but it possesses uniqueness in many aspects.People's demands for personalized clothing quality,styles,and matching are constantly growing,making digital transformation crucial for the clothing industry.Faced with massive clothing data,clothing recommendation systems play a crucial role as a key link,including personalized recommendations,enhancing user experience,and increasing revenue,bringing numerous practical benefits to both users and businesses,and simultaneously driving the industry towards intelligent and efficient development.This article combines the key aspects of clothing recommendation systems and summarizes the general process and related technologies for creating clothing recommendation systems,including data collection and preprocessing,feature engineering,and model construction.It provides a detailed overview of key technologies in both traditional recommendation techniques and deep learning applied in the field of clothing recommendations,analyzing the application and expansion of various algorithms.In terms of application,clothing recommendation systems are widely used in e-commerce platforms and clothing styling recommendation apps,offering users convenient shopping and styling suggestions.Finally,based on the application areas and development trends of clothing recommendation systems,it explores the pressing issues that clothing recommendation systems need to address and future innovative directions.
万方数据
维普
