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Privacy-preserving collaborative filtering

机译:隐私保护协作过滤

摘要

A recommender system can generate a predicted item rating for one user by performing collaborative filtering on item ratings from other users. The recommender system can include a client device (204) that interfaces with a server (202) to obtain a predicted item rating for a local user. The client device can generate a standardized ratings vector for the user, and computes a group identifier for the user based on the standardized ratings vector. The system also generates a noisy ratings vector for the local user, and sends a user-ratings snapshot to a recommendation server that includes the group identifier and the noisy ratings vector. The recommender system can also include the recommendation server that generates a predicted item rating for the user by performing collaborative filtering on ratings vectors from a plurality of other users that belong to the same ratings group.
机译:推荐器系统可以通过对其他用户的项目评分执行协作过滤来为一个用户生成预测的项目评分。推荐器系统可以包括与服务器(202)对接以获得针对本地用户的预测项目等级的客户端设备(204)。客户端设备可以为用户生成标准化的评级向量,并且基于标准化的评级向量为用户计算组标识符。该系统还为本地用户生成一个嘈杂的评分向量,并将用户评分快照发送给推荐服务器,其中包括组标识符和嘈杂的评分向量。推荐器系统还可以包括推荐服务器,该推荐服务器通过对来自属于相同评级组的多个其他用户的评级向量执行协作过滤来为用户生成预测的项目评级。

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