Patents by Inventor Karan Singh Rekhi

Karan Singh Rekhi has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 9976864
    Abstract: One or more techniques and/or systems are provided for providing a recommendation and/or a travel interface based upon a predicted travel intent. For example, a set of user signals (e.g., search queries, calendar information, social network data, etc.) may be evaluated to determine the predicted travel intent for a user to travel to a destination. A recommendation may be provided based upon the predicted travel intent. For example, images, news stories, advertisements, events, attractions, travel accommodation (e.g., hotel, car, and/or flight reservation functionality) and/or other information and functionality associated with the destination may be provided through the recommendation. The recommendation may be provided through an alert, a mobile app, a website, a travel interface, and/or a variety of other interfaces. The predicted travel intent may be used to modify information provided by a website, an operating system, and/or apps (e.g., a news app may display information about the destination).
    Type: Grant
    Filed: April 7, 2017
    Date of Patent: May 22, 2018
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Zachary Adam Kahn, Karan Singh Rekhi, Gautam Kedia
  • Publication number: 20170211945
    Abstract: One or more techniques and/or systems are provided for providing a recommendation and/or a travel interface based upon a predicted travel intent. For example, a set of user signals (e.g., search queries, calendar information, social network data, etc.) may be evaluated to determine the predicted travel intent for a user to travel to a destination. A recommendation may be provided based upon the predicted travel intent. For example, images, news stories, advertisements, events, attractions, travel accommodation (e.g., hotel, car, and/or flight reservation functionality) and/or other information and functionality associated with the destination may be provided through the recommendation. The recommendation may be provided through an alert, a mobile app, a website, a travel interface, and/or a variety of other interfaces. The predicted travel intent may be used to modify information provided by a website, an operating system, and/or apps (e.g., a news app may display information about the destination).
    Type: Application
    Filed: April 7, 2017
    Publication date: July 27, 2017
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Zachary Adam Kahn, Karan Singh Rekhi, Gautam Kedia
  • Patent number: 9618343
    Abstract: One or more techniques and/or systems are provided for providing a recommendation and/or a travel interface based upon a predicted travel intent. For example, a set of user signals (e.g., search queries, calendar information, social network data, etc.) may be evaluated to determine the predicted travel intent for a user to travel to a destination. A recommendation may be provided based upon the predicted travel intent. For example, images, news stories, advertisements, events, attractions, travel accommodation (e.g., hotel, car, and/or flight reservation functionality) and/or other information and functionality associated with the destination may be provided through the recommendation. The recommendation may be provided through an alert, a mobile app, a website, a travel interface, and/or a variety of other interfaces. The predicted travel intent may be used to modify information provided by a website, an operating system, and/or apps (e.g., a news app may display information about the destination).
    Type: Grant
    Filed: December 12, 2013
    Date of Patent: April 11, 2017
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Zachary Adam Kahn, Karan Singh Rekhi, Gautam Kedia
  • Publication number: 20170034010
    Abstract: Technologies are described herein for changelog transformation and correlation in a multi-tenant cloud service. Components within the multi-tenant cloud service generate changelogs that describe changes made to hardware or software components within the multi-tenant cloud service. The changelogs are received and transformed from different schemas into a common schema. A central change management service (“CCMS”) exposes a network service application programming interface (“API”), or other type of interface, through which other network services can obtain the changelogs that have been transformed into the common schema. For example, services can obtain changelogs in order to correlate changes to anomalies or other events taking place in the multi-tenant cloud service, to identify upstream or downstream components that might be impacted by a change, to provide a user interface for viewing the changelogs, the correlation, or the potential impact of a change, and/or to perform other types of functions.
    Type: Application
    Filed: July 31, 2015
    Publication date: February 2, 2017
    Inventors: Eddie W.M. Fong, Nagaraju Palla, Ricardo Soares Stern, Rajmohan Rajagopalan, Bhavin J. Shah, Narendra Babu Alagiriswamy, Karan Singh Rekhi, Parikshit Patidar
  • Publication number: 20170032268
    Abstract: Technologies are described herein for identification and presentation of changelogs relevant to a tenant of a multi-tenant cloud service. Change feature extraction is performed on changelogs associated with a tenant of the multi-tenant cloud service to identify features associated with the changelogs. Machine learning based classification can then be performed on the changelogs to classify the changelogs. Misclassification correction might also be performed on the classified changelogs. Machine learning can also be utilized to identify a subset of the changelogs as being relevant to the tenant. A user interface (UI) can then be generated and provided to the tenant that includes the subset of the changelogs. The tenant's interaction with the changelogs presented in the UI can be monitored and data describing the interaction can be used to modify machine learning models utilized for machine learning change classification and for determining the relevance of a changelog to the tenant.
    Type: Application
    Filed: July 31, 2015
    Publication date: February 2, 2017
    Inventors: Rajmohan Rajagopalan, Ricardo Soares Stern, Mufaddal M. Pratapgarhwala, Karan Singh Rekhi, Bhavin J. Shah, Eddie W.M. Fong, Nagaraju Palla, Parikshit Patidar
  • Publication number: 20160350658
    Abstract: Examples of the present disclosure describe systems and methods for improving the recommendations provided to a user by a recommendation system using viewed content as implicit feedback. In some aspects, attention models are created/updated to infer the user attention of a user that has viewed or is viewing content on a computing device. The attention model may be used to convert inferences of user attention into inferences of user satisfaction with the viewed content. The inferences of user satisfaction may be used to generate inferences of fatigue with the viewed content. The inferences of user satisfaction and inferences of user fatigue may then be used as implicit feedback to improve the content selection, content triggering and/or content presentation by the recommendation system. Other examples are also described.
    Type: Application
    Filed: June 1, 2015
    Publication date: December 1, 2016
    Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Gautam Kedia, Kieran McDonald, Qi Guo, Abhishek Jha, Karan Singh Rekhi, Zachary Kahn, Aidan Crook
  • Publication number: 20150269152
    Abstract: One or more techniques and/or systems are provided for ranking recommendations within a set of recommendations. For example, a set of locational relevance boundaries may be generated and/or configured for ranking the set of recommendation. For example, a locational relevance boundary may adjust a rank of a recommendation using a rank influence (e.g., a linear function, a step function, a numerical value, and/or any other function used to increase, decrease, or assign a value to the rank based upon a current location of the user). The locational relevance boundary may be applied based upon the current location of the user corresponding to one or more threshold distances from a target recommendation location. For example, a logarithmic function may be applied to a rank of a theater recommendation when the user is less than 1.2 miles from the theater. Ranked recommendations may be provided to the user.
    Type: Application
    Filed: March 18, 2014
    Publication date: September 24, 2015
    Inventors: Karan Singh Rekhi, Abhishek Jha, Gautam Kedia, Kieran Richard McDonald, Andrew P. McGovern
  • Publication number: 20150168150
    Abstract: One or more techniques and/or systems are provided for providing a recommendation and/or a travel interface based upon a predicted travel intent. For example, a set of user signals (e.g., search queries, calendar information, social network data, etc.) may be evaluated to determine the predicted travel intent for a user to travel to a destination. A recommendation may be provided based upon the predicted travel intent. For example, images, news stories, advertisements, events, attractions, travel accommodation (e.g., hotel, car, and/or flight reservation functionality) and/or other information and functionality associated with the destination may be provided through the recommendation. The recommendation may be provided through an alert, a mobile app, a website, a travel interface, and/or a variety of other interfaces. The predicted travel intent may be used to modify information provided by a website, an operating system, and/or apps (e.g., a news app may display information about the destination).
    Type: Application
    Filed: December 12, 2013
    Publication date: June 18, 2015
    Applicant: Microsoft Corporation
    Inventors: Zachary Adam Kahn, Karan Singh Rekhi, Gautam Kedia
  • Publication number: 20140372423
    Abstract: Architecture that performs the automatic modeling of user preferences for entities (a personal entity preference model) based on user's actions such as search history and temporal search behavior to determine content on the web relevant and of interest to a given user at any given time. Explicit and implicit user responses (e.g., notification clicks, ignore, dismiss, unsubscribe, notification dwell) are used to update the model of user entity preferences. The user entity preference model is used to order notifications based on predicted relevance. Additionally, the user personal entity preference model and implicit responses of user are used to decide timing and frequency of notifications.
    Type: Application
    Filed: June 13, 2013
    Publication date: December 18, 2014
    Inventors: Rangan Majumder, Kyrylo Tropin, Türker Keskinpala, Karan Singh Rekhi