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MANAGING DATASETS OF A COGNITIVE STORAGE SYSTEM WITH A SPIKING NEURAL NETWORK

机译:带有神经网络的认知存储系统的数据集管理

摘要

A computer-implemented method for managing datasets of a storage system is provided, wherein the datasets have respective sets of metadata, the method including: successively feeding first sets of metadata to a spiking neural network (SNN), the first sets of metadata fed corresponding to datasets of the storage system that are labeled with respect to classes they belong to, so as to be associated with class labels, for the SNN to learn representations of said classes in terms of connection weights that weight the metadata fed; successively feeding second sets of metadata to the SNN, the second sets of metadata corresponding to unlabeled datasets of the storage system, for the SNN to infer class labels for the unlabeled datasets, based on the second sets of metadata fed and the representations learned; and managing datasets in the storage system, based on class labels of the datasets, these including the inferred class labels.
机译:提供了一种用于管理存储系统的数据集的计算机实现的方法,其中,数据集具有各自的元数据集,该方法包括:将第一组元数据连续地馈送到尖峰神经网络(SNN),第一组元数据对应地馈给相对于存储系统的数据集,该数据集针对它们所属的类别进行了标记,以便与类别标签相关联,以便SNN根据连接权重来学习所述类别的表示,该权重对所馈送的元数据进行加权;根据所馈送的第二组元数据和学习到的表示,将与存储系统中未标记数据集相对应的第二组元数据依次馈送给SNN,以供SNN推断未标记数据集的类标签。根据数据集的类别标签(包括推断的类别标签)来管理和管理存储系统中的数据集。

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