请大神翻译下以下文字,不要用机器翻译哦,要求准确点,谢谢

发布网友发布时间：2022-05-06 13:07

共2个回答

热心网友时间：2022-06-30 16:21

Recommendation Algorithm, as one of the most important methods of Information Filtering (IF), is considered for having a very high potential in resolving the current "information overload" problem. One of the most prominent applications of Recommendation Algorithm is in the Electric Commerce (E-Commerce) field. The Recommendation Algorithm method can suggest possible procts that may be of interest to a customer (such as books and CDs) based on the customer's interest and preferences. It identifies the potential needs of the users, and turn them into actual needs, in order to reach the targets of improving the sales volume of the proct. The personalized Recommender System is a high-end Business Intelligence platform that is based on a Mass Data Mining approach, in order to help E-Commerce sites in supporting completely customized customer shopping experience and decision-making, as well as providing information. This suggests the high significance of developing the Recommendation Algorithm.

This report starts with introces the state quo of Recommendation Algorithm, suggests the importance of studying the subject. It also examines the development of Recommendation Algorithm and the existing problems, and outlines the similiarity comparasion methods. Based on the outlines, it provides a comprehensive overview of Collaborative Filtering and studies the existing conditions and issues. It then focuses on the examination of the Collaborative Filtering Recommendation Algorithm based on Uncertain Neighbors and Item Rating Prediction, and presents the detailed methodology in support of the Recommendation Algorithm and its formulas. At last, as realized in the Collaborative Filtering Algorithm based on Uncertain Neighbors and Item Rating Prediction, two algorithms are developed using MATLAB language to be implemented in MATLAB.
The results of the study unveils that, under the conditions of the data collected by this report, the accuracy rate of the Uncertain Neighbors approach is higher than the Item Rating Prediction approach. Also, when the Uncertain Neighbors approach is being applied, the accuracy rate becomes higher as the number of the participants in the study increases; and the accuracy rate becomes constant as the number of participants reaches to a certain value.

全是自己人工翻译的。

热心网友时间：2022-06-30 16:22

Served as a kind of important means of information filtering, Recommendation of Technology is considered the method that has the great potentiality to the solve the problems of the current information overload. The most typical application of recommended technology was focused on the electronic business field. Complying with the users' interest , hobbies, Recommended technology can recommend the commodities that are possibled to attract the customer's interest and satisfy the customers (such as , books, videos ) To dig the potential demand of the customers to transform it to actual demand