公开(公告)号：US20180082124A1

公开(公告)日：2018-03-22

申请号：US15559020

申请日：2015-06-02

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

Inventor： Tong Zhang ,  Georgia Koutrika ,  Jerry Liu ,  Steven J Simske

IPC: G06K9/00 ,  G11B27/34 ,  H04N5/445 ,  G06K9/62

CPC classification number: G06K9/00744 ,  G06K9/00718 ,  G06K9/00765 ,  G06K9/6253 ,  G06Q50/10 ,  G09B5/06 ,  G11B27/28 ,  G11B27/34 ,  H04N5/44504 ,  H04N21/4788 ,  H04N21/8549

Abstract: Examples associated with keyframe annotation are disclosed. One example includes extracting a set of keyframes from a video presentation. A subset of the keyframes is selected to present to a user based on a user preference. Annotations are generated for the subset of the keyframes. The annotations are personalized to the user. The subset of the keyframes and the annotations are presented to the user.

公开(公告)号：US20170235822A1

公开(公告)日：2017-08-17

申请号：US15518756

申请日：2015-01-23

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

Inventor： Lei LIU ,  Georgia Koutrika ,  Jerry Liu

IPC: G06F17/30 ,  G06Q50/20

CPC classification number: G06F16/337 ,  G06Q10/0631 ,  G06Q10/105 ,  G06Q50/20

Abstract: Examples relate to grouping students using content fields. Student data including a plurality of content fields is obtained. Each content field of the plurality of content fields includes a value that represents an unstructured marking linked to a content data collection. Student profiles are generated by assigning a student identification number to each of the plurality of content fields. Each of the student identification numbers are organized into at least one student group by analyzing the set of student profiles.

公开(公告)号：US20170221163A1

公开(公告)日：2017-08-03

申请号：US15500917

申请日：2014-07-31

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

Inventor： Lei Liu ,  Georgia Koutrika ,  Jerry Liu

IPC: G06Q50/20 ,  G09B5/08 ,  G09B7/02 ,  G06Q10/06 ,  G06Q10/10

CPC classification number: G06Q50/20 ,  G06Q10/063112 ,  G06Q10/103 ,  G09B5/00 ,  G09B5/08 ,  G09B7/02

Abstract: Examples disclosed herein relate to creating a heterogeneous learner group. In one implementation, a processor associates a selected learner with a group of learners based on a value of a factor associated with the group of learners compared to a value of the factor associated with the selected learner. For example, the value associated with the selected learner may be indicative of a strength compared to the value associated with the group of learners. The processor may output information related to a heterogeneous learner group created from the group of learners and the selected learner.