COMPUTING SYSTEM FOR IDENTIFYING AND USING BENCHMARK ATTRIBUTE TYPES AMONG SIMILAR ENTITIES IN DIFFERENT DATASETS

原文（中国語）

A method including identifying a target dataset within a number of datasets. Each of the datasets includes a number of similar attribute types. A first clustering model is applied, according to a similarity attribute type, to the datasets and the target dataset to generate a cluster of datasets. A second clustering model is applied to the cluster to generate a first subcluster and a second subcluster. The second clustering model clusters according to a performance attribute type, different than the similarity attribute type. A benchmark attribute type, comparable to a target attribute type of the target dataset, is identified in at least one of the first subcluster and the second subcluster. An outlier value for the benchmark attribute type of an outlier dataset in the at least one of the first subcluster and the second subcluster is identified. The benchmark attribute type and the outlier value are returned.