公开(公告)号：US11256998B2

公开(公告)日：2022-02-22

申请号：US15414387

申请日：2017-01-24

Applicant: Intel Corporation

Inventor： Omri Mendels ,  Boris Kodner ,  Ariel Benou ,  Oded Vainas ,  Avi Samoucha ,  Tali Zvi

IPC: G06N5/04 ,  G16H10/60 ,  G16H50/70 ,  G16H50/20 ,  G16H40/67 ,  G16H20/30 ,  G06N7/00 ,  G06Q10/06

Abstract: Various systems and methods for processing activity data with a knowledge engine to generate actionable insights for a human subject are described. These actionable insights may include identifying a most likely action given a particular state of the human subject, identifying a most likely state in which the human subject performs a particular activity, or identifying anomalies in human activity patterns. In an example, an electronic processing system operates the knowledge engine with operations that: identify patterns of activity using clustering of events, identify meaningful patterns of activity from the patterns of activity based on co-occurrence of characteristics for respective events, rank the identified meaningful patterns of activity based on confidence and support of respective patterns to occur for a human subject, and generate a personalization action (such as an action for a software application) based on the ranked, identified meaningful patterns of activity.

公开(公告)号：US20180211175A1

公开(公告)日：2018-07-26

申请号：US15414387

申请日：2017-01-24

Applicant: Intel Corporation

Inventor： Omri Mendels ,  Boris Kodner ,  Ariel Benou ,  Oded Vainas ,  Avi Samoucha ,  Tali Zvi

IPC: G06N7/00 ,  G06N5/02

CPC classification number: G06N5/048 ,  G06Q10/06 ,  G06Q10/063 ,  G16H10/60 ,  G16H20/30 ,  G16H40/67 ,  G16H50/20 ,  G16H50/70

Abstract: Various systems and methods for processing activity data with a knowledge engine to generate actionable insights for a human subject are described. These actionable insights may include identifying a most likely action given a particular state of the human subject, identifying a most likely state in which the human subject performs a particular activity, or identifying anomalies in human activity patterns. In an example, an electronic processing system operates the knowledge engine with operations that: identify patterns of activity using clustering of events, identify meaningful patterns of activity from the patterns of activity based on co-occurrence of characteristics for respective events, rank the identified meaningful patterns of activity based on confidence and support of respective patterns to occur for a human subject, and generate a personalization action (such as an action for a software application) based on the ranked, identified meaningful patterns of activity.