公开(公告)号：US12242928B1

公开(公告)日：2025-03-04

申请号：US16824480

申请日：2020-03-19

Applicant: Amazon Technologies, Inc.

Inventor： Xianshun Chen ,  Kai Liu ,  Nikhil Anand Navali ,  Archiman Dutta

IPC: G06N20/00 ,  G06N5/01

Abstract: Multiple distinct control descriptors, each specifying an algorithm and values of one or more parameters of the algorithm, are created. A plurality of tuples, each indicating a respective record of a data set and a respective descriptor, are generated. The tuples are distributed among a plurality of compute resources such that the number of distinct descriptors indicated in the tuples received at a given resource is below a threshold. The algorithm is executed in accordance with the descriptors' parameters at individual compute resources.

公开(公告)号：US11675766B1

公开(公告)日：2023-06-13

申请号：US16808162

申请日：2020-03-03

Applicant: Amazon Technologies, Inc.

Inventor： Xianshun Chen ,  Kai Liu ,  Nikhil Anand Navali ,  Archiman Dutta

IPC: G06F16/22 ,  G06F16/28 ,  G06F16/901

CPC classification number: G06F16/2246 ,  G06F16/285 ,  G06F16/9024

Abstract: A hierarchical representation of an input data set comprising similarity scores for respective entity pairs is generated iteratively. In a particular iteration, clusters are obtained from a subset of the iteration's input entity pairs which satisfy a similarity criterion, and then spanning trees are generated for at least some of the clusters. An indication of at least a representative pair of one or more of the clusters is added to the hierarchical representation in the iteration. The hierarchical representation is used to respond to clustering requests.

公开(公告)号：US11514321B1

公开(公告)日：2022-11-29

申请号：US16900620

申请日：2020-06-12

Applicant: Amazon Technologies, Inc.

Inventor： Xianshun Chen ,  Zahed Patel ,  Kai Liu ,  Nikhil Anand Navali ,  Archiman Dutta

IPC: G06E1/00 ,  G06N3/08 ,  G06N3/04

Abstract: Entity record pairs are extracted from a selected cluster of entity records. Attribute value pairs are obtained from the entity record pairs. Labels are assigned to the attribute value pairs based at least in part on entity-level similarity scores of the entity records from which the attribute value pairs were obtained. A machine learning model is trained, using a data set which includes at least some attribute value pairs to which the labels are assigned, to generate attribute similarity scores for pairs of attribute values.