公开(公告)号：US20170212788A1

公开(公告)日：2017-07-27

申请号：US15500510

申请日：2014-10-23

Applicant: Hewlett-Packard Development Company, L.P.

Inventor： Jun Zeng ,  Sushant Bhattacharya ,  Gary J Dispoto ,  Will Allen ,  Patrick O Sandfort ,  Francisco Jose Oblea Ramirez ,  Steven Simske

IPC: G06F9/50 ,  G06F9/48 ,  G06F3/12

CPC classification number: G06F9/505 ,  G06F3/121 ,  G06F3/1231 ,  G06F9/4881 ,  G06F2209/501

Abstract: Examples herein disclose receiving a service request including a latency associated with a publication of a result of the service request. The examples disclose computing a workload for the service request and identifying multiple resources which are to perform the service request by applying the latency to the multiple resources.

公开(公告)号：US20170039297A1

公开(公告)日：2017-02-09

申请号：US15101879

申请日：2013-12-29

Applicant: HEWLETT-PACKARD DEVELOPMENT COMPANY, L.P.

Inventor： Georgia Koutrika ,  Lei Liu ,  Jerry Liu ,  Steven Simske

IPC: G06F17/30 ,  G06N99/00

CPC classification number: G06F16/9024 ,  G06F16/93 ,  G06F17/21 ,  G06N20/00

Abstract: A learning graph is generated for documents according to a sequencing approach. The learning graph includes nodes corresponding to the documents and edges. Each edge connects two of the nodes and indicates a sequencing relationship between two of the documents to which the two of the nodes correspond that specifies an order in which the two of the documents are to be reviewed in satisfaction of the learning goal. The learning graph is a directed graph specifying a learning path through the documents to achieve a learning goal in relation to a subject.

Abstract translation: 根据排序方法为文档生成学习图。 学习图包括对应于文档和边缘的节点。 每个边缘连接两个节点，并指示两个节点对应的两个文档之间的排序关系，指定两个文档的顺序，以满足学习目标的要求。 学习图是指定通过文档的学习路径以实现与主题相关的学习目标的有向图。

公开(公告)号：US11263478B2

公开(公告)日：2022-03-01

申请号：US15779838

申请日：2016-04-07

Applicant: Hewlett-Packard Development Company, L.P.

Inventor： Stephen Pollard ,  Guy Adams ,  Steven Simske

IPC: G06K9/62 ,  G06K9/46 ,  G06K9/00

Abstract: An example system includes a feature extraction engine. The feature extraction engine is to determine a plurality of scale-dependent features for a portion of a target. The system also includes a signature-generation engine to select a subset of the plurality of scale-dependent features based on a strength of each feature. The signature-generation engine also is to store a numeric representation of the portion of the target and the subset of the plurality of scale-dependent features.

公开(公告)号：US20180365519A1

公开(公告)日：2018-12-20

申请号：US15779838

申请日：2016-04-07

Applicant: Hewlett-Packard Development Company, L.P.

Inventor： Stephen Pollard ,  Guy Adams ,  Steven Simske

IPC: G06K9/62 ,  G06K9/46

Abstract: An example system includes a feature extraction engine. The feature extraction engine is to determine a plurality of scale-dependent features for a portion of a target. The system also includes a signature-generation engine to select a subset of the plurality of scale-dependent features based on a strength of each feature. The signature-generation engine also is to store a numeric representation of the portion of the target and the subset of the plurality of scale-dependent features.

公开(公告)号：US20220156510A1

公开(公告)日：2022-05-19

申请号：US17592761

申请日：2022-02-04

Applicant: Hewlett-Packard Development Company, L.P.

Inventor： Stephen Pollard ,  Guy Adams ,  Steven Simske

IPC: G06K9/62 ,  G06V10/40 ,  G06V10/75 ,  G06V20/80

Abstract: An example system includes a feature extraction engine. The feature extraction engine is to determine a plurality of scale-dependent features for a portion of a target. The system also includes a signature-generation engine to select a subset of the plurality of scale-dependent features based on a strength of each feature. The signature-generation engine also is to store a numeric representation of the portion of the target and the subset of the plurality of scale-dependent features.