Personalized User Interface Elements Recommendation System

A review of recommendation system research based on knowledge graph

“…The recommendation systems have alleviated the problem of information overload [1] to some extent, but traditional recommendation algorithms have problems such as interpretability, data sparsity, scalability, diversity, cold start, etc. With the development of deep learning, machine learning, graph neural networks, knowledge graphs, and other research, researchers are combining them with recommendation systems to make more accurate recommendations.…”

“…Massive information generated on the Internet has become an essential source of information in the daily life of most people. The explosive growth of Internet data not only provides people with a vast information search space but also leads to the phenomenon of information overload [1], which has dramatically exceeded people's acceptance range, making it more difficult for people to obtain structured knowledge from it. The emergence of recommendation systems [2] has solved this problem well, and their academic and industrial value have been widely concerned.…”

Research and Design of a Job Search Service Platform Based on Recommendation Algorithm

“…Foreign research mostly focuses on algorithms that recommend users based on their level of interest. For example, algorithms such as KNN and LDA are widely used in personalized recommendations, analyze user historical behavior data to identify their interests and preferences and thereby bring more personalized recommendation results to users [3] . In addition, some researchers have also attempted to improve recommendation accuracy and efficiency by applying machine learning technology to recommendation systems and continuously learning and optimizing algorithms.…”