首页> 外国专利> EFFICIENT AND FAULT-TOLERANT DISTRIBUTED ALGORITHM FOR LEARNING LATENT FACTOR MODELS THROUGH MATRIX FACTORIZATION

EFFICIENT AND FAULT-TOLERANT DISTRIBUTED ALGORITHM FOR LEARNING LATENT FACTOR MODELS THROUGH MATRIX FACTORIZATION

机译:通过矩阵分解来学习潜在因素模型的高效容错分布式算法

摘要

A method for estimating model parameters. The method comprises receiving a data set related to a plurality of users and associated content, partitioning the data set into a plurality of sub data sets in accordance with the users so that data associated with each user are not partitioned into more than one sub data set, storing each of the sub data sets in a separate one of a plurality of user data storages, each of said data storages being coupled with a separate one of a plurality of estimators, storing content associated with the plurality of users in a content storage, where the content storage is coupled to the plurality of estimators so that the content in the content storage is shared by the estimators, and estimating, asynchronously by each estimator, one or more parameters associated with a model based on data from one of the sub data sets.
机译:一种估计模型参数的方法。该方法包括:接收与多个用户和相关内容有关的数据集;根据用户将数据集划分为多个子数据集,以使与每个用户相关的数据不被划分为一个以上的子数据集。将每个子数据集存储在多个用户数据存储区中的一个单独的一个中,每个所述数据存储区与多个估计器中的一个独立的耦合,将与多个用户相关联的内容存储在一个内容存储中,其中内容存储耦合到多个估计器,以便由估计器共享内容存储中的内容,并由每个估计器异步地基于来自子数据之一的数据估计与模型关联的一个或多个参数套。

著录项

相似文献

  • 专利
  • 外文文献
  • 中文文献
获取专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号