Corey Layne Reese

US Patent:

20130024449, Jan 24, 2013

Filed:

Jul 19, 2012

Appl. No.:

13/553684

Inventors:

Sourav Chatterji - Fremont CA, US
Jeremy Ryan Schiff - Portola Valley CA, US
Corey Layne Reese - Portola Valley CA, US
Paul Kenneth Twohey - Palo Alto CA, US

Assignee:

Ness Computing, Inc. - Los Altos CA

International Classification:

G06F 17/30

US Classification:

707728, 707E17014

Abstract:

Embodiment of the invention relate to a computer-implemented method for providing augmented searches for entities to a user, the method comprising obtaining, at a server computer operated by an entity search system, user data related to a user, and obtaining entity data related to a plurality of entities. Then, the entity search system receives a query for a search for relevant entities from the user. The method then further comprises searching for a set of relevant entities based on the query, entity data, and user data, determining a set of criteria for an initial order of relevance, and determining an order of relevance of the set of relevant entities based on the set of criteria. The set of relevant entities or order of relevance may be augmented by obtaining feedback data from the user, thereby providing an augmented search for relevant entities to the user.

US Patent:

20130024456, Jan 24, 2013

Filed:

Jul 19, 2012

Appl. No.:

13/553646

Inventors:

Scott Paul Goodson - La Honda CA, US
Sourav Chatterji - Fremont CA, US
Jeremy Ryan Schiff - Portola Valley CA, US
Corey Layne Reese - Portola Valley CA, US
Paul Kenneth Twohey - Palo Alto CA, US

Assignee:

Ness Computing, Inc. - Los Altos CA

International Classification:

G06F 17/30

US Classification:

707740, 707E17089, 707E17032

Abstract:

Embodiments of the invention relate to a category based navigation system obtaining user data related to a plurality of users relevant to the primary user. The method further comprises obtaining entity data associated with an entity in a plurality of entities. The category based navigation system then determines one or more entities relevant to the primary user, and determines an initial order of relevance of a set of relevant entities. The method further comprises categorizing and displaying the set of relevant entities with an initial categorization on a user device to the primary user. The category based navigation system may then obtain, via the user device, user feedback, adjust the initial categorization and initial order of relevance based on the user feedback; and display the adjusted categorization and adjusted order of relevance of the set of relevant entities to the primary user on the user device.

US Patent:

20130024464, Jan 24, 2013

Filed:

Jul 19, 2012

Appl. No.:

13/553599

Inventors:

Christopher Eric Shogo Berner - Sunnyvale CA, US
Jeremy Ryan Schiff - Portola Valley CA, US
Corey Layne Reese - Portola Valley CA, US
Paul Kenneth Twohey - Palo Alto CA, US

Assignee:

Ness Computing, Inc. - Los Altos CA

International Classification:

G06F 17/30

US Classification:

707749, 707E17084

Abstract:

Embodiments of the invention relate to a computer-implemented method for generating explanatory data from a personalized recommendations process for a primary user based at least on stored data about the primary user. The method comprises a server computer obtaining data related to one or more users who are relevant to the primary user, then determining at least one group of users relevant to the primary user. The server computer also obtains data related to one or more entities, determines one or more entities relevant to the primary user, and associates the at least one relevant group of users with the one or more relevant entities. One or more potential candidate factors are generated. A set of factors are selected from the one or more potential candidate factors, wherein the potential candidate factors are used as explanatory data to determine recommendations to the primary user.

US Patent:

20130024465, Jan 24, 2013

Filed:

Jul 19, 2012

Appl. No.:

13/553703

Inventors:

Jeremy Ryan Schiff - Portola Valley CA, US
Sourav Chatterji - Fremont CA, US
Corey Layne Reese - Portola Valley CA, US
Steven Charles Schlansker - Los Altos CA, US
Leejay Wu - Mountain View CA, US
Paul Kenneth Twohey - Palo Alto CA, US

Assignee:

Ness Computing, Inc. - Los Altos CA

International Classification:

G06F 17/30

US Classification:

707749, 707E17005

Abstract:

Embodiments of the invention relate to methods and systems for evaluating entities for a target user, the method comprising obtaining, at a server computer, entity data from a plurality of data sources. The entity data is then stored in an entity database. The method further comprises merging the entity data from the plurality of data sources, mapping the entity data to a corresponding entity, and differentiating the entity. Then a relevance is determined associated with the entity data and data source. The method further comprises generating a set of entity evaluations to the target user using the relevance, determining a set of one or more entities relevant to the primary user based on the entity data, user data, and the relevance, with an initial order of relevance, and displaying, on a user device, the set of relevant entities to the target user in the order of relevance.

US Patent:

20120095862, Apr 19, 2012

Filed:

Oct 14, 2011

Appl. No.:

13/274226

Inventors:

Jeremy Ryan Schiff - Portola Valley CA, US
Paul Kenneth Twohey - Palo Alto CA, US
Steven Charles Schlansker - Los Altos CA, US
Leejay Wu - Mountain View CA, US
Corey Reese - Portola Valley CA, US
Sourav Chatterji - Fremont CA, US

Assignee:

Ness Computing, Inc. (a Delaware Corportaion) - Los Altos CA

International Classification:

G06Q 30/02

US Classification:

705 267

Abstract:

Embodiments of the invention relate to a computer-implemented method and system for generating personalized recommendations for a target user based at least on stored data about the target user. The method comprises obtaining, at the server computer, data from a plurality of data sources, including entity data associated with a plurality of entities, stored in an entity database, or personal data associated with a plurality of users, stored in a user database. The personalized recommendations system then merges the entity data or personal data and maps the entity or personal data to a corresponding entity or target user, respectively. The entity or personal data is differentiated, a relevance is determined, a weight is assigned to the data and corresponding source to canonicalize the data, the respective databases are updated with the corresponding data, and then a set of personalized recommendations to the target user is generated using the updated databases.

US Patent:

20120095863, Apr 19, 2012

Filed:

Oct 14, 2011

Appl. No.:

13/274235

Inventors:

Jeremy Ryan Schiff - Portola Valley CA, US
Corey Reese - Portola Valley CA, US
Yige Wang - East Palo Alto CA, US
Scott Goodson - La Honda CA, US
Paul Kenneth Twohey - Palo Alto CA, US

Assignee:

Ness Computing, Inc. - Los Altos CA

International Classification:

G06Q 30/02

US Classification:

705 267

Abstract:

Embodiments of the invention relate to a computer-implemented method and system for providing personalized recommendations for a target user based at least on stored data about the target user. The method comprises obtaining a plurality of feedback data from a plurality of users, wherein the feedback data comprises an indication of a media object, a response obtained from target user related to the feedback data, and at least one demographic data element associated with the target user. A set of personalized recommendations for the target user are identified based at least on stored data about the target user and the feedback data related to the user. The personalized recommendations system identifies media objects to potentially provide to the target user, and selects or filters the identified media objects to form a set of personalized media objects associated with the set of personalized recommendations.

US Patent:

20220292575, Sep 15, 2022

Filed:

May 31, 2022

Appl. No.:

17/828689

Inventors:

- San Francisco CA, US
Paul Kenneth Twohey - Palo Alto CA, US
Steven Charles Schlansker - Los Altos CA, US
Leejay Wu - Mountain View CA, US
Corey Reese - Portola Valley CA, US
Sourav Chatterji - Fremont CA, US

International Classification:

G06Q 30/06
G06Q 30/02

Abstract:

Embodiments of the invention relate to a computer-implemented method and system for generating personalized recommendations for a target user based at least on stored data about the target user. The method comprises obtaining, at the server computer, data from a plurality of data sources, including entity data associated with a plurality of entities, stored in an entity database, or personal data associated with a plurality of users, stored in a user database. The personalized recommendations system then merges the entity data or personal data and maps the entity or personal data to a corresponding entity or target user, respectively. The entity or personal data is differentiated, a relevance is determined, a weight is assigned to the data and corresponding source to canonicalize the data, the respective databases are updated with the corresponding data, and then a set of personalized recommendations to the target user is generated using the updated databases.

US Patent:

20210149891, May 20, 2021

Filed:

Nov 23, 2020

Appl. No.:

17/101558

Inventors:

- San Francisco CA, US
Sourav Chatterji - Fremont CA, US
Corey Layne Reese - Portola Valley CA, US
Steven Charles Schlansker - Los Altos CA, US
Leejay Wu - Mountain View CA, US
Paul Kenneth Twohey - Palo Alto CA, US

International Classification:

G06F 16/248
G06F 16/951
G06F 16/954
G06F 16/955
G06F 16/9535
G06F 16/2457

Abstract:

Embodiments of the invention relate to methods and systems for evaluating entities for a target user, the method comprising obtaining, at a server computer, entity data from a plurality of data sources. The entity data is then stored in an entity database. The method further comprises merging the entity data from the plurality of data sources, mapping the entity data to a corresponding entity, and differentiating the entity. Then a relevance is determined associated with the entity data and data source. The method further comprises generating a set of entity evaluations to the target user using the relevance, determining a set of one or more entities relevant to the primary user based on the entity data, user data, and the relevance, with an initial order of relevance, and displaying, on a user device, the set of relevant entities to the target user in the order of relevance.