协同过滤系统的第二个效果是收集的信息是基于哪种内容、你喜欢还是不喜欢的评注，并根据您提交并参加投票的习惯，这些正是用户数据概况。
The second aspect of the (CF) system collects information on what kind of content and commentary you like and dislike, and based on your submission and voting habits, it does user-data-profiling.
不管用什么方法，协同过滤或基于item相似的推荐都是不会被原谅的商业工具，假阳性般的错误会很快地让用户流失。
Regardless of the method, collaborative filtering or inherent properties of things - recommendations are an unforgiving business, where false positives quickly turn users off.
协同过滤是目前最成功的一种推荐算法，它能够基于其他用户的观点帮助人们作出选择。
Collaborative filtering recommendation algorithm can make choices based on the opinions of other people. It is the most successful technology for building recommender systems to date.
应用推荐