公开(公告)号：US10579752B2

公开(公告)日：2020-03-03

申请号：US15309836

申请日：2014-05-12

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Inbal Tadeski ,  Ron Banner ,  Omer Barkol

IPC: G06F17/50 ,  G06F16/335 ,  G06F17/16 ,  G06Q30/02 ,  G06F16/9535 ,  G06Q10/06

Abstract: Described herein are techniques for generating a model based on input. In an example, a first model can be generated based on decomposing a rating matrix into a product of two matrices U and V, where U represents correlations between users and a plurality of factors and V represents correlations between items and the plurality of factors. At least some of the users and items can be grouped into groups according to the correlations. Input on one or more of the groups can be received. A second model can be generated based on the input on the one or more of the groups.

公开(公告)号：US10353927B2

公开(公告)日：2019-07-16

申请号：US15324043

申请日：2014-07-10

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Inbal Tadeski ,  Eli Hayoon ,  Hadas Kogan

IPC: G06F16/22 ,  G06F16/23 ,  G06F16/28 ,  G06F16/2457

Abstract: In an example, columns in a data table may be categorized according to a data type based upon an analysis of data elements contained in each column with a grammar file. The data type of a column be may be categorized as one of a general data type and a specific data type. In addition, the grammar file may be expanded by at least one of adding a data element to the grammar file in response to a column being categorized as a specific data type and inserting a new data type to the grammar file in response to a column being categorized as a general data type.

公开(公告)号：US20170199940A1

公开(公告)日：2017-07-13

申请号：US15325957

申请日：2014-10-30

Applicant: Inbal TADESKI ,  Hadas KOGAN ,  Eli HAYOON ,  Eyal HAYUN ,  Doron SHAKED ,  Gil ELGRABLY ,  Olga SHAIN ,  HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Inbal Tadeski ,  Hadas Kogan ,  Eli Hayoon ,  Eyal Hayun ,  Doron Shaked ,  Gil Elgrably ,  Olga Shain

IPC: G06F17/30 ,  G06F17/22 ,  G06F3/0482

CPC classification number: G06F16/9024 ,  G06F3/0482 ,  G06F16/24578 ,  G06F16/904 ,  G06F17/2235 ,  G06F17/2247 ,  G06F17/2264

Abstract: Data entries can include values for each of a number of features that each have a number of permissible or possible values. The features and the permissible values thereof are ranked based on a graph constructed from the features and the permissible values. The data entries can include textual data for free-text features that do not have permissible values or possible values, and new features created based on information extracted from the textual data, where nodes and edges are added to the graph from these new features. Graphical elements corresponding to the features and graphical representations based on frequencies of the permissible values of the features can be displayed.

公开(公告)号：US20170161358A1

公开(公告)日：2017-06-08

申请号：US15324043

申请日：2014-07-10

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Inbal Tadeski ,  Eli Hayoon ,  Hadas Kogan

IPC: G06F17/30

CPC classification number: G06F16/285 ,  G06F16/221 ,  G06F16/2365 ,  G06F16/24578

Abstract: In an example, columns in a data table may be categorized according to a data type based upon an analysis of data elements contained in each column with a grammar file. The data type of a column be may be categorized as one of a general data type and a specific data type. In addition, the grammar file may be expanded by at least one of adding a data element to the grammar file in response to a column being categorized as a specific data type and inserting a new data type to the grammar file in response to a column being categorized as a general data type.

公开(公告)号：US20170147721A1

公开(公告)日：2017-05-25

申请号：US15309836

申请日：2014-05-12

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Inbal Tadeski ,  Ron Banner ,  Omer Barkol

IPC: G06F17/50 ,  G06F17/16

CPC classification number: G06F17/5009 ,  G06F16/337 ,  G06F16/9535 ,  G06F17/16 ,  G06Q10/067 ,  G06Q30/0201 ,  G06Q30/0282

Abstract: Described herein are techniques for generating a model based on input. In an example, a first model can be generated based on decomposing a rating matrix into a product of two matrices U and V, where U represents correlations between users and a plurality of factors and V represents correlations between items and the plurality of factors. At least some of the users and items can be grouped into groups according to the correlations. Input on one or more of the groups can be received. A second model can be generated based on the input on the one or more of the groups.