Patents Examined by Kakali Chaki
  • Patent number: 9767411
    Abstract: A system includes a free itemset generation unit to generate a set of free itemsets, each having a frequency in the database greater than or equal to a predetermined threshold value set in advance, a valid rule candidate generation unit to generate rule candidates and store the generated rule candidates, and a rule minimality decision unit to check minimality of each of the generated rule candidates and output the generated rule candidate to an output apparatus when the generated rule candidate is determined to be minimal.
    Type: Grant
    Filed: May 13, 2013
    Date of Patent: September 19, 2017
    Assignee: NEC Corporation
    Inventor: Hiroki Nakayama
  • Patent number: 9760828
    Abstract: A mechanism is provided, in a data processing system comprising a processor and a memory configured to implement a question and answer system (QA), for utilizing temporal indicators to weight semantic values. A set of temporal characteristics is identified of a set of initial candidate answers. For each initial candidate answer in the set of initial candidate answers: a distance value is generated for each of the set of temporal characteristics of the set of initial candidate answers, a multiplier value is determined with which to weight an initial confidence score associated with the initial candidate answer using the distance value; a sentiment value is determined of the initial candidate answer, and a final weight value is determined using the multiplier value, the sentiment value, and the initial confidence score associated with the initial candidate answer. A set of temporally refined candidate answers is then provided using the determined final weight values.
    Type: Grant
    Filed: September 22, 2015
    Date of Patent: September 12, 2017
    Assignee: International Business Machines Corporation
    Inventors: John P. Bufe, III, Alexander Pikovsky, Timothy P. Winkler
  • Patent number: 9754208
    Abstract: A method of validating rules configured to be utilized in an information extraction application, including: receiving a plurality of labeled samples in a training database; for each of the rules in the rule database: (a) determining, for each of the data points of the plurality of labeled samples in the training database to which the rule applies, whether applying the rule to the data point has a positive or negative impact on matching an output for the data point based on the rule to the assured output of the labeled sample corresponding to the data point; (b) generating positive impact information for the rule based on the positive voters; (c) generating negative impact information for the rule based on the negative voters; and (d) determining a metric for the rule based on the quantity of the negative voters and the quantity of the positive voters; ranking the rules based on the metrics corresponding to the rules; and sending to a user for refinement one or more flagged rules of the rules that have a lowes
    Type: Grant
    Filed: September 2, 2014
    Date of Patent: September 5, 2017
    Assignee: WAL-MART STORES, INC.
    Inventors: Jun Xie, Chong Sun, Fan Yang, Narasimhan Rampalli
  • Patent number: 9753986
    Abstract: Method, system, and computer program product to analyze a plurality of candidate answers identified as responsive to a question presented to a deep question answering system, by computing a first feature score for a first feature of an item of evidence, of a plurality of items of evidence, the first feature score being based on at least one attribute of the first feature, the item of evidence relating to a first candidate answer, of the plurality of candidate answers, and computing a merged feature score for the first candidate answer by applying the first feature score to a second feature score for a second feature of the item of evidence.
    Type: Grant
    Filed: December 17, 2012
    Date of Patent: September 5, 2017
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Joel C. Dubbels, Thomas J. Eggebraaten, Mark G. Megerian, William C. Rapp, Richard J. Stevens, Patrick M. Wildt, Eric W. Will
  • Patent number: 9754209
    Abstract: A method is used in managing knowledge-based authentication systems. Questions are created from organization based information. The questions are evaluated based on a set of parameters. Based on the evaluation, a set of questions is selected from the questions and a set of responses is selected for each question of the set of questions for a scenario. A user is authenticated in the scenario using the set of questions.
    Type: Grant
    Filed: September 27, 2012
    Date of Patent: September 5, 2017
    Assignee: EMC IP Holding Company LLC
    Inventors: Boris Kronrod, Ido Zilberberg
  • Patent number: 9754215
    Abstract: System, method, and computer program product to identify relevant features in a deep question answering system, by classifying a first case received by the deep question answering system, and, while training the deep question answering system to answer the first case, identifying a first feature in the first case, computing a first feature score for the first feature, the first feature score indicating a relevance of the first feature in generating a correct response to the first case, and, identifying the first feature as relevant in answering the classified first case upon determining that the first feature score exceeds a relevance threshold.
    Type: Grant
    Filed: December 17, 2012
    Date of Patent: September 5, 2017
    Assignee: SINOEAST CONCEPT LIMITED
    Inventors: Adam T. Clark, Mark G. Megerian, John E. Petri, Richard J. Stevens
  • Patent number: 9753696
    Abstract: The subject disclosure is directed towards crowd-based approach to boosting the correctness of a computer program. Results from candidate programs obtained from a first crowd and which may be blended with one another into synthesized programs are sent to a second crowd for evaluation. Based upon the results, a training set evolves and programs are filtered based upon fitness. The process of blending and fitness evaluation with an evolved training set may be iteratively repeated to find a most fit program.
    Type: Grant
    Filed: March 14, 2014
    Date of Patent: September 5, 2017
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Benjamin Livshits, Robert A. Cochran
  • Patent number: 9754203
    Abstract: A device, comprising: an array of cells, wherein the cells are arranged in columns and rows; wherein each cell comprises a memristive device; an interfacing circuit that is coupled to each cell of the array of cells; wherein the interfacing circuit is arranged to: receive or generate first variables and second variables; generate memristive device input signals that once provided to memristive devices of the array will cause a change in a state variable of each of the memristive devices of the cells of the array, wherein the change in the state variable of each of the memristive devices of the cells of array reflects a product of one of the first variables and one of the second variables; provide the memristive device input signals to memristive devices of the array; and receive output signals that are a function of at least products of the first variables and the second variables.
    Type: Grant
    Filed: March 19, 2014
    Date of Patent: September 5, 2017
    Assignee: TECHNION RESEARCH AND DEVELOPMENT FOUNDATION LTD.
    Inventors: Dotan Di Castro, Daniel Soudry, Shahar Kvatinsky, Asaf Gal, Avinoam Kolodny
  • Patent number: 9747548
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for computing a layer output for a convolutional neural network layer, the method comprising: receiving a plurality of activation inputs; forming a plurality of vector inputs from the plurality of activation inputs, each vector input comprising values from a distinct region within the multi-dimensional matrix; sending the plurality of vector inputs to one or more cells along a first dimension of the systolic array; generating a plurality of rotated kernel structures from each of the plurality of kernel; sending each kernel structure and each rotated kernel structure to one or more cells along a second dimension of the systolic array; causing the systolic array to generate an accumulated output based on the plurality of value inputs and the plurality of kernels; and generating the layer output from the accumulated output.
    Type: Grant
    Filed: December 22, 2016
    Date of Patent: August 29, 2017
    Assignee: Google Inc.
    Inventors: Jonathan Ross, Gregory Michael Thorson
  • Patent number: 9747547
    Abstract: A nonlinear neuron classifier comprising a neuron array including a plurality of neuron chips each including a plurality of neurons of variable length and variable depth, the chips processing input vectors of variable length and variable depth that are input into the classifier for comparison against vectors stored in the classifier, wherein an NSP flag is set for a plurality of the neurons to indicate that only that plurality of neurons is to participate in the vector calculations. A virtual content addressable memory flag is set for certain of the neuron chips to enable functions including fast readout of data from the chips. Results of vector calculations are aggregated for fast readout for a host computer interfacing with the classifier.
    Type: Grant
    Filed: January 21, 2016
    Date of Patent: August 29, 2017
    Assignee: in2H2
    Inventors: Bruce Kent McCormick, William Harry Nagel, Christopher John McCormick, Mickey Lee Fandrich, Vardan Movsisyan, Matthew McCormick
  • Patent number: 9741098
    Abstract: A digital camera includes an image optimization engine configured to generate an optimized image based on a raw image captured by the digital camera. The image optimization engine implements one or more machine learning engines in order to select rendering algorithms and rendering algorithm arguments that may then be used to render the raw image.
    Type: Grant
    Filed: October 12, 2012
    Date of Patent: August 22, 2017
    Assignee: NVIDIA Corporation
    Inventor: Michael Brian Cox
  • Patent number: 9734449
    Abstract: Methods and apparatus are provided for run-time user control of system-generated content. A user is presented with the system-generated content and can configure one or more rules at run-time. The rules identify one or more automated actions to perform upon the system-generated content when one or more conditions are satisfied. The automated actions are executed upon the system-generated content when the one or more conditions are satisfied. The exemplary automated actions may comprise transform, retrieve, update and alert. The conditions can specify, for example, when to perform the automated actions. Active tags may optionally be attached to or embedded directly in the system-generated content or in a document containing the system-generated content. Tools are optionally provided to allow a user to manage active tags.
    Type: Grant
    Filed: July 30, 2009
    Date of Patent: August 15, 2017
    Assignee: International Business Machines Corporation
    Inventors: Jennifer Lai, Jie Lu, Lauren G. Wilcox
  • Patent number: 9727826
    Abstract: Disclosed are various embodiments for using contrarian machine learning models to compensate for selection bias. Both a primary machine learning model and a contrarian machine learning model may be trained for selecting sets of items based at least in part on the same training data. However, the contrarian machine learning model is specially trained to avoid selecting items that are selected by the primary machine learning model. Items selected by the primary model and items selected by the contrarian model are presented to users as recommendations. Both models are updated based at least in part on user selections of items. Ultimately, the use of the contrarian model avoids causing the primary model to degenerate to picking random items due to reinforcement resulting from a bias in favor of selecting items that have been recommended.
    Type: Grant
    Filed: September 9, 2014
    Date of Patent: August 8, 2017
    Assignee: Amazon Technologies, Inc.
    Inventor: Ian Alan Lindstrom
  • Patent number: 9727821
    Abstract: A dataset including at least one temporal event sequence is collected. A one-class sequence classifier f(x) that obtains a decision boundary is statistically learned. At least one new temporal event sequence is evaluated, wherein the at least one new temporal event sequence is outside of the dataset. It is determined whether the at least one new temporal event sequence is one of a normal sequence or an abnormal sequence based on the evaluation. Numerous additional aspects are disclosed.
    Type: Grant
    Filed: August 16, 2013
    Date of Patent: August 8, 2017
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Ching-Yung Lin, Yale Song, Zhen Wen
  • Patent number: 9727818
    Abstract: The modeling of an impression effect may include generating a content item impression effect distribution. A classification model may be used to determine a period of the content item impression effect distribution based on one or more accessed impression effect parameters. A value for a content item may be determined based, at least in part, on the determined period and a bid associated with the content item. A content item may be selected based on the determined value and data to display the selected content item may be transmitted. In some instances, the determined period may be used to determine or select predictive model for the determined period that outputs a factor to modify the determined value.
    Type: Grant
    Filed: February 23, 2014
    Date of Patent: August 8, 2017
    Assignee: Google Inc.
    Inventor: Yifang Liu
  • Patent number: 9721214
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a model using parameter server shards. One of the methods includes receiving, at a parameter server shard configured to maintain values of a disjoint partition of the parameters of the model, a succession of respective requests for parameter values from each of a plurality of replicas of the model; in response to each request, downloading a current value of each requested parameter to the replica from which the request was received; receiving a succession of uploads, each upload including respective delta values for each of the parameters in the partition maintained by the shard; and updating values of the parameters in the partition maintained by the parameter server shard repeatedly based on the uploads of delta values to generate current parameter values.
    Type: Grant
    Filed: August 8, 2016
    Date of Patent: August 1, 2017
    Assignee: Google Inc.
    Inventors: Gregory S. Corrado, Kai Chen, Jeffrey A. Dean, Samy Bengio, Rajat Monga, Matthieu Devin
  • Patent number: 9721204
    Abstract: An artificial neural network may be configured to test the impact of certain input parameters. To improve testing efficiency and to avoid test runs that may not alter system performance, the effect of input parameters on neurons or groups of neurons may be determined to classify the neurons into groups based on the impact of certain parameters on those groups. Groups may be ordered serially and/or in parallel based on the interconnected nature of the groups and whether the output of neurons in one group may affect the operation of another. Parameters not affecting group performance may be pruned as inputs to that particular group prior to running system tests, thereby conserving processing resources during testing.
    Type: Grant
    Filed: October 28, 2013
    Date of Patent: August 1, 2017
    Assignee: QUALCOMM Incorporated
    Inventors: Michael Campos, Casimir Matthew Wierzynski, Bardia Fallah Behabadi
  • Patent number: 9710764
    Abstract: Roughly described, individuals in both a training system and in a production system include a label field in their rule outputs. Positions entered by an individual are maintained in a status record for the individual, including the label output by the rule which triggered entry of that position. Rules that assert exiting or partial exiting of a position also output the label from the rule which triggered the assertion, and are effective only so far as matching positions exist or remain in the individual's status record, including a matching label. Labels present in the status record also can be referenced in conditions of a rule. During evolution, a rule's output label is subject to crossover and/or mutation just like the conditions and output assertions.
    Type: Grant
    Filed: March 13, 2014
    Date of Patent: July 18, 2017
    Assignee: SENTIENT TECHNOLOGIES (BARBADOS) LIMITED
    Inventors: Babak Hodjat, Hormoz Shahrzad, Kaivan Kamali, Daniel E. Fink
  • Patent number: 9704097
    Abstract: Training data for training a neural network usable for electronic sentiment analysis can be automatically constructed. For example, an electronic communication usable for training the neural network and including multiple characters can be received. A sentiment dictionary including multiple expressions mapped to multiple sentiment values representing different sentiments can be received. Each expression in the sentiment dictionary can be mapped to a corresponding sentiment value. An overall sentiment for the electronic communication can be determined using the sentiment dictionary. Training data usable for training the neural network can be automatically constructed based on the overall sentiment of the electronic communication. The neural network can be trained using the training data. A second electronic communication including an unknown sentiment can be received. At least one sentiment associated with the second electronic communication can be determined using the neural network.
    Type: Grant
    Filed: December 11, 2015
    Date of Patent: July 11, 2017
    Assignees: SAS INSTITUTE INC., NORTH CAROLINA STATE UNIVERSITY
    Inventors: Ravinder Devarajan, Jordan Riley Benson, David James Caira, Saratendu Sethi, James Allen Cox, Christopher G. Healey, Gowtham Dinakaran, Kalpesh Padia
  • Patent number: 9691022
    Abstract: The present invention generally relates to systems and methods for visual process analysis. The disclosed techniques can include: obtaining a theoretical and an empirical process model, generating a theoretical process layout corresponding to the theoretical process model, where the theoretical process layout is generated using a layout algorithm, generating an empirical process layout corresponding to the empirical process model, where the empirical process layout is generated using the layout algorithm, superposing the empirical process layout onto the theoretical process layout, such that a superposition layout is generated, annotating the superposition layout based on ugliness indicators, such that an annotated superposition layout is generated, and causing the annotated superposition layout to be displayed.
    Type: Grant
    Filed: April 14, 2014
    Date of Patent: June 27, 2017
    Assignee: Xerox Corporation
    Inventors: Andres Quiroz Hernandez, Yasmine Charif, Julien Bourdaillet