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.
Recommendation Engine That Processes Data Including User Data To Provide Recommendations And Explanations For The Recommendations To A User
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.
Method And Apparatus For Quickly Evaluating Entities
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.
Computer System And Method For Analyzing Data Sets And Generating Personalized Recommendations
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.
Computer System And Method For Analyzing Data Sets And Providing Personalized Recommendations
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.
Computer System And Method For Analyzing Data Sets And Generating Personalized Recommendations
- 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.
Method And Apparatus For Quickly Evaluating Entities
- 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
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.
Magnetic, Reconfigurable, Plush Toy Apparatus And Method
- Portola Valley CA, US Corey Reese - Portola Valley CA, US
International Classification:
A63H 3/16 A63H 3/02 A63H 3/46
Abstract:
A reconfigurable toy includes a plush body and an attachable appendage. The plush body contains a first magnetic attachment assembly including a flexible retaining element, a base layer, a magnetic layer, and an acoustic feedback layer. The attachable appendage includes a second magnetic attachment assembly. Magnetic attraction between the first magnetic attachment assembly and the second magnetic attachment assembly removably couples the attachable appendage to the plush body. A corresponding method is also disclosed and claimed herein.
Name / Title
Company / Classification
Phones & Addresses
Corey Reese Chief Executive Officer
Ness Computing LLC Custom Computer Programing
1 Montgomery St, San Francisco, CA 94104 4300 El Camino Real, Los Altos, CA 94022
Three Kings Construction Group LLP Philadelphia, PA 2010 to 2011 Office ManagerSav-A-Lot Philadelphia, PA 2009 to 2010 Produce ClerkPride Enterprises Inc Philadelphia, PA 2007 to 2009 Administrative Assistant
docuseries offering a glimpse into the worlds most innovative homes and the visionaries who created them. The 10 hourlong episodes come from Matt Tyrnauer (Valentino: The Last Emperor), Corey Reese of Altimeter Films, Matthew Weaver (Chefs Table), Ian Orefice and Bruce Gersh from Time Inc. Productions
evice, somewhat like Foursquares tips. On Yelp, people can sort through many restaurants that have three or four stars, but it can be hard to differentiate between them. Were trying to make it really easy to make a decision, says Corey Reese, CEO and co-founder of Ness Computing.