Patents by Inventor Elad Yom-Tov

Elad Yom-Tov 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: 10320817
    Abstract: A system for detecting an attack by a virtual or physical machine on one or more auto-generated websites is provided. The system includes a processor, a memory, and an application. The application is stored in the memory and includes instructions, which are executable by the processor. The instructions are configured to: access an index of a search engine server computer and determine uniform resource locators (URLs) of auto-generated websites, where the auto-generated websites include the one or more auto-generated websites; and access Internet protocol (IP) address-URL entries stored in a domain name system server computer.
    Type: Grant
    Filed: November 16, 2016
    Date of Patent: June 11, 2019
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Hani Neuvirth-Telem, Elad Yom-Tov, Royi Ronen, Daniel Alon Hilevich
  • Publication number: 20190130099
    Abstract: A system includes identification of a data source of a production environment, the data source storing authentic data, generation of simulated data of the data source, reception of a request for data of the data source from a requesting system in the production environment and, in response to the received request, providing of the simulated data to the requesting system. In some aspects, the simulated data is provided to the requesting system if it is determined that the request is related to an electronic attack, and the authentic data of the data source is provided to the requesting system if it is not determined that the request is related to an electronic attack.
    Type: Application
    Filed: November 1, 2017
    Publication date: May 2, 2019
    Inventors: Elad YOM-TOV, Hani Hana NEUVIRTH, Ron MATCHORO, Nir ROSENFELD
  • Publication number: 20180366024
    Abstract: A method that includes accessing, from a database, a correlation between a first variable and a second variable; retrieving a list of suggested user behavior modifications for the correlation; selecting a user behavior modification from the list; presenting the selected user behavior modification to a computer device; receiving adherence data indicating a level of adherence by the user to the user behavior modification; and reevaluating the correlation between the first variable and the second variable based on the adherence data. The method may improve the determination of causality, versus merely correlation, between the variables. This determination may permit for improved recommendations to individuals to achieve a desired user outcome.
    Type: Application
    Filed: June 14, 2017
    Publication date: December 20, 2018
    Inventors: Elad Yom-Tov, Hadas Bitran, Shahar Yekutiel, Gil Shacham, Tachen Chester Ni, Ryen W. White
  • Publication number: 20180342004
    Abstract: Computerized systems and methods are provided for determining cumulative success-based recommendations for repeat users. One such method includes determining user and item latent-features based on matrix factorization applied to matrices that include recommendation and feedback events. The feedback events indicate previously provided user preferences for at least a portion of the items. An item-recommendation policy is determined based on a cumulative metric that includes an expected value for the accumulation of stochastic user-item rewards associated with future (or subsequent) recommendations. The accumulation of the rewards is based on the user latent-features, the item latent-features, and the previous rewards included in the feedback events. Machine learning, such as reinforcement learning (RL), is employed to determine the item-recommendation policy based on the feedback events.
    Type: Application
    Filed: May 25, 2017
    Publication date: November 29, 2018
    Inventors: Elad Yom-Tov, Assaf Hallak, Noam Koenigstein
  • Publication number: 20180329997
    Abstract: A computer-implemented filtering method comprising: receiving a set of propositions, each comprising a respective linguistic description expressed by a respective user; forming an input matrix of lexical components vs. propositions, wherein rows in the input matrix represent the propositions and columns in the input matrix represent lexical components in the respective descriptions; performing a matrix factorization on the input matrix to reveal latent clusters of the lexical components and/or propositions; filtering the set of propositions based on one or more of the latent clusters; and outputting a result of the filtering to a target user.
    Type: Application
    Filed: June 30, 2017
    Publication date: November 15, 2018
    Inventors: Eran GAT, Moshe GOLDSTINE, Elad YOM-TOV
  • Publication number: 20180144154
    Abstract: Examples are disclosed that relate to providing healthcare-related information. One example provides a computing device comprising a logic machine and a storage machine holding instructions executable by the logic machine to receive an input of information regarding a health state of a user, obtain, based upon the information regarding the health state of the user, an inference of a possible health condition of the user, output a notification of the inference, the notification comprising a first representation of the inference, receive data representing a mechanism for authorizing a healthcare practitioner to access a second representation of the inference, and output a user-selectable control for triggering the mechanism. The instructions may be further executable to receive an input via the user-selectable control triggering the mechanism, and, in response, send authorization to provide the healthcare practitioner with access to the second representation of the inference.
    Type: Application
    Filed: November 22, 2016
    Publication date: May 24, 2018
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Gil Shacham, Ryen William White, Hadas Bitran, Shahar Yekutiel, Elad Yom-Tov, Christopher R. Jones, Todd Eric Holmdahl
  • Publication number: 20180139215
    Abstract: A system for detecting an attack by a virtual or physical machine on one or more auto-generated websites is provided. The system includes a processor, a memory, and an application. The application is stored in the memory and includes instructions, which are executable by the processor. The instructions are configured to: access an index of a search engine server computer and determine uniform resource locators (URLs) of auto-generated websites, where the auto-generated websites include the one or more auto-generated websites; and access Internet protocol (IP) address-URL entries stored in a domain name system server computer.
    Type: Application
    Filed: November 16, 2016
    Publication date: May 17, 2018
    Inventors: Hani Neuvirth-Telem, Elad Yom-Tov, Royi Ronen, Daniel Alon Hilevich
  • Publication number: 20180089372
    Abstract: Examples are disclosed herein that relate to modifying an analysis of personal behavior based on determining a subset of personal data to be non-routine. One example provides a computing device configured to receive personal data relating to personal behavior of a user, receive contextual data regarding the personal data, determine a subset of the personal data to be non-routine based upon the contextual data, and modify an analysis of personal behavior based upon the subset of the personal data determined to be non-routine.
    Type: Application
    Filed: September 29, 2016
    Publication date: March 29, 2018
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Hadas Bitran, Gil Shacham, Arie Schwartzman, Ryen William White, Tachen C. Ni, Girish Sthanu Nathan, Elad Yom-Tov, Jessica Lundin, Shahar Yekutiel
  • Publication number: 20170359362
    Abstract: In an example embodiment, a computer-implemented method comprises obtaining labels from messages associated with an email service provider, wherein the labels indicate for each message IP how many spam and non-spam messages have been received; obtaining network data features from a cloud service provider; providing the labels and network data features to a machine learning application; generating a prediction model representing an algorithm for determining whether a particular set of network data features are spam or not; applying the prediction model to network data features for an unlabeled message; and generating an output of the prediction model indicating a likelihood that the unlabeled message is spam.
    Type: Application
    Filed: November 30, 2016
    Publication date: December 14, 2017
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Ori Kashi, Philip Newman, Daniel Alon, Elad Yom-Tov, Hani Neuvirth, Royi Ronen
  • Patent number: 9811992
    Abstract: A system for providing care to a ward that alerts a caregiver of the caregiver's capacity to deal competently with the ward's needs.
    Type: Grant
    Filed: June 6, 2016
    Date of Patent: November 7, 2017
    Assignee: Microsoft Technology Licensing, LLC.
    Inventors: Hani Neuvirth-Telem, Elad Yom-Tov, Hadas Bitran, Omer Chechik, Amit Hilbuch
  • Publication number: 20170161127
    Abstract: A system for identifying abnormal resource usage in a data center is provided. In some embodiments, the system employs a prediction model for each of a plurality of resources and an abnormal resource usage criterion. For each of a plurality of resources of the data center, the system retrieves current resource usage data for a current time and past resource usage data for that resource. The system then extracts features from the past resource usage data for that resource, predicts using the prediction model for that resource usage data for the current time based on the extracted features, and determines an error between the predicted resource usage data and the current resource usage data. After determining the error data for the resources, the system determines whether errors satisfy the abnormal resource usage criterion. If so, the system indicates that an abnormal resource usage has occurred.
    Type: Application
    Filed: December 20, 2016
    Publication date: June 8, 2017
    Inventors: Hani Neuvirth-Telem, Amit Hilbuch, Shay Baruch Nahum, Yehuda Finkelstein, Daniel Alon, Elad Yom-Tov
  • Patent number: 9665460
    Abstract: A system for identifying abnormal resource usage in a data center is provided. In some embodiments, the system employs a prediction model for each of a plurality of resources and an abnormal resource usage criterion. For each of a plurality of resources of the data center, the system retrieves current resource usage data for a current time and past resource usage data for that resource. The system then extracts features from the past resource usage data for that resource, predicts using the prediction model for that resource usage data for the current time based on the extracted features, and determines an error between the predicted resource usage data and the current resource usage data. After determining the error data for the resources, the system determines whether errors satisfy the abnormal resource usage criterion. If so, the system indicates that an abnormal resource usage has occurred.
    Type: Grant
    Filed: May 26, 2015
    Date of Patent: May 30, 2017
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Hani Neuvirth-Telem, Amit Hilbuch, Shay Baruch Nahum, Yehuda Finkelstein, Daniel Alon, Elad Yom-Tov
  • Publication number: 20170039335
    Abstract: A network-accessible computer includes a network-communications interface, configured to receive health metrics of a user over a computer network. The network-accessible computer also includes a logic machine, which is configured to localize the user in a virtual space based on the health metrics, identify k nearest neighbors in the virtual space having k shortest Euclidean distances to the user, and generate a health insight comparing the user to the k nearest neighbors. The network-communications interface is further configured to send the health insight to a computing device associated with the user via the computer network.
    Type: Application
    Filed: December 2, 2015
    Publication date: February 9, 2017
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Ansari Mohammed Ismail, Hadas Bitran, Royi Ronen, Ohad Jassin, Elad Yom-Tov, Andrew Lindsay Dumovic, Haithem Albadawi, Farah Shariff, Todd Holmdahl
  • Publication number: 20170039332
    Abstract: A method for presenting health notifications begins with creating a plurality of different health notifications, each conveying the same type of information. Each of the different health notifications is provided to a plurality of different users, each user categorized with user health metrics. Post-health notification user activity is tracked for each of the different users. A machine-learning classification machine is trained with tracked user activity, along with corresponding user health metrics, for each of the different health notifications. When provided with user health metrics received from a health-monitoring computing device associated with a user, the machine-learning classification machine chooses a selected health notification for the user from among the different health notifications, the selected notification determined to be more likely than any of the other health notifications to elicit a healthy response from the user. The selected health notification is then sent to the user.
    Type: Application
    Filed: December 14, 2015
    Publication date: February 9, 2017
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Elad Yom-Tov, Hadas Bitran, Nazia Zaman, Brian Bilodeau, Katherine Winant Osborne, David A. Wickert, Ran Gilad-Bachrach, Gerrit Hendrik Hofmeester, Farah Shariff
  • Publication number: 20160350198
    Abstract: A system for identifying abnormal resource usage in a data center is provided. In some embodiments, the system employs a prediction model for each of a plurality of resources and an abnormal resource usage criterion. For each of a plurality of resources of the data center, the system retrieves current resource usage data for a current time and past resource usage data for that resource. The system then extracts features from the past resource usage data for that resource, predicts using the prediction model for that resource usage data for the current time based on the extracted features, and determines an error between the predicted resource usage data and the current resource usage data. After determining the error data for the resources, the system determines whether errors satisfy the abnormal resource usage criterion. If so, the system indicates that an abnormal resource usage has occurred.
    Type: Application
    Filed: May 26, 2015
    Publication date: December 1, 2016
    Inventors: Hani Neuvirth-Telem, Amit Hilbuch, Shay Baruch Nahum, Yehuda Finkelstein, Daniel Alon, Elad Yom-Tov
  • Publication number: 20160342755
    Abstract: The subject disclosure is directed towards monitoring user behavior on a computerized device for any deviation from normal or acceptable behavior that is likely to affect the user's mental state. A prediction model corresponding to features of one or more mental states may be compared with features based upon current user behavior. If the user's current behavior presents a mental state indicative of an uncharacteristic deviation from the normal or acceptable behavior, descriptive data associated with that mental state may be presented to the user in addition to a trusted individual, such as a health care professional.
    Type: Application
    Filed: August 1, 2016
    Publication date: November 24, 2016
    Inventors: Elad Yom-Tov, Eric J. Horvitz, Ryen William White, Munmun De Choudhury, Scott J. Counts
  • Patent number: 9427185
    Abstract: The subject disclosure is directed towards monitoring user behavior on a computerized device for any deviation from normal or acceptable behavior that is likely to affect the user's mental state. A prediction model corresponding to features of one or more mental states may be compared with features based upon current user behavior. If the user's current behavior presents a mental state indicative of an uncharacteristic deviation from the normal or acceptable behavior, descriptive data associated with that mental state may be presented to the user in addition to a trusted individual, such as a health care professional.
    Type: Grant
    Filed: June 20, 2013
    Date of Patent: August 30, 2016
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Elad Yom-Tov, Eric J. Horvitz, Ryen William White, Munmun De Choudhury, Scott J Counts
  • Publication number: 20160104094
    Abstract: This document relates to meeting evaluation. One example determines previous meeting attributes of previous meetings that were attended by a user or to which the user was invited, and obtains implicit feedback about the previous meetings from a device of the user. The example includes training a predictive algorithm to evaluate future meetings for the user using the previous meeting attributes and the implicit feedback about the previous meetings.
    Type: Application
    Filed: October 9, 2014
    Publication date: April 14, 2016
    Applicant: Microsoft Corporation
    Inventors: Elad Yom-Tov, Mariano R. Schain, Moshe Tennenholtz
  • Patent number: 9208451
    Abstract: A computer-implemented method, an apparatus and a computer program for automatically extracting useful information for functional verification. The method comprising performing repeatedly both operating an instruction generator associated with a Design Under Test (DUT), whereby a generated instruction is determined, the generated instruction having one or more instruction attributes; and collecting information relating to the generated instruction. Based on the generated instruction and the collected information, a classification technique is utilized to classify the information based on the instruction attributes.
    Type: Grant
    Filed: February 5, 2014
    Date of Patent: December 8, 2015
    Assignee: GlobalFoundries Inc.
    Inventors: Yoav Katz, Michal Rimon, Elad Yom-Tov, Avi Ziv
  • Publication number: 20150310529
    Abstract: One or more web-behavior-augmented recommendation servers augment catalog interaction data between consumers and a catalog of products with collected online web behavior data associated with individual users. The online web behavior data represents online web behavior of the each consumer outside of the catalog of products and can improve the accuracy of product recommendations, which then be presented to an individual consumer via a computer user interface.
    Type: Application
    Filed: April 28, 2014
    Publication date: October 29, 2015
    Applicant: Microsoft Corporation
    Inventors: Royi Ronen, Elad Yom-Tov, Elad Ziklik, Gal Lavee