Patents by Inventor Gregory Purdy
Gregory Purdy 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).
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Patent number: 10916003Abstract: An image quality scorer machine accesses a candidate image to be analyzed for visual quality. The image quality scorer machine generates a visual quality score of the candidate image by first generating a prediction of a similarity score for the candidate image. The predicted similarly score of the candidate image may be generated by a process including inputting the candidate image into a neural network that has been trained to detect a set of image features in the candidate image and then to generate a corresponding predicted similarity score based on degrees to which the image features in the set are present in the candidate image. The image quality scorer machine derives the visual quality score based on the predicted similarity score outputted by the neural network. Accordingly, the image quality score machine may provide or store the generated visual quality score of candidate image for subsequent usage.Type: GrantFiled: March 20, 2018Date of Patent: February 9, 2021Assignee: Uber Technologies, Inc.Inventors: Thibault Doutre, David Gregory Purdy, Jason Byron Yosinski
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Publication number: 20190295240Abstract: An image quality scorer machine accesses a candidate image to be analyzed for visual quality. The image quality scorer machine generates a visual quality score of the candidate image by first generating a prediction of a similarity score for the candidate image. The predicted similarly score of the candidate image may be generated by a process including inputting the candidate image into a neural network that has been trained to detect a set of image features in the candidate image and then to generate a corresponding predicted similarity score based on degrees to which the image features in the set are present in the candidate image. The image quality scorer machine derives the visual quality score based on the predicted similarity score outputted by the neural network. Accordingly, the image quality score machine may provide or store the generated visual quality score of candidate image for subsequent usage.Type: ApplicationFiled: March 20, 2018Publication date: September 26, 2019Inventors: Thibault Doutre, David Gregory Purdy, Jason Byron Yosinski
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Patent number: 9767092Abstract: A method of extracting information from text within a natural language understanding system can include processing a text input through at least one statistical model for each of a plurality of features to be extracted from the text input. For each feature, at least one value can be determined, at least in part, using the statistical model associated with the feature. One value for each feature can be combined to create a complex information target. The complex information target can be output.Type: GrantFiled: August 15, 2016Date of Patent: September 19, 2017Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Publication number: 20160350281Abstract: A method of extracting information from text within a natural language understanding system can include processing a text input through at least one statistical model for each of a plurality of features to be extracted from the text input. For each feature, at least one value can be determined, at least in part, using the statistical model associated with the feature. One value for each feature can be combined to create a complex information target. The complex information target can be output.Type: ApplicationFiled: August 15, 2016Publication date: December 1, 2016Inventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Patent number: 9454525Abstract: A method of extracting information from text within a natural language understanding system can include processing a text input through at least one statistical model for each of a plurality of features to be extracted from the text input. For each feature, at least one value can be determined, at least in part, using the statistical model associated with the feature. One value for each feature can be combined to create a complex information target. The complex information target can be output.Type: GrantFiled: May 20, 2013Date of Patent: September 27, 2016Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Patent number: 9342588Abstract: A method of creating a statistical classification model for a classifier within a natural language understanding system can include processing training data using an existing statistical classification model. Sentences of the training data correctly classified into a selected class of the statistical classification model can be selected. The selected sentences of the training data can be assigned to a fringe group or a core group according to confidence score. The training data can be updated by associating the fringe group with a fringe subclass of the selected class and the core group with a core subclass of the selected class. A new statistical classification model can be built from the updated training data. The new statistical classification model can be output.Type: GrantFiled: June 18, 2007Date of Patent: May 17, 2016Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Patent number: 9058319Abstract: A method of classifying text input for use with a natural language understanding system can include determining classification information including a primary classification and one or more secondary classifications for a received text input using a statistical classification model (statistical model). A statistical classification sub-model (statistical sub-model) can be selectively built according to a model generation criterion applied to the classification information. The method further can include selecting the primary classification or the secondary classification for the text input as a final classification according to the statistical sub-model and outputting the final classification for the text input.Type: GrantFiled: June 18, 2007Date of Patent: June 16, 2015Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Publication number: 20130262093Abstract: A method of extracting information from text within a natural language understanding system can include processing a text input through at least one statistical model for each of a plurality of features to be extracted from the text input. For each feature, at least one value can be determined, at least in part, using the statistical model associated with the feature. One value for each feature can be combined to create a complex information target. The complex information target can be output.Type: ApplicationFiled: May 20, 2013Publication date: October 3, 2013Applicant: International Business Machines CorporationInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Patent number: 8521511Abstract: A method of extracting information from text within a natural language understanding system can include processing a text input through at least one statistical model for each of a plurality of features to be extracted from the text input. For each feature, at least one value can be determined, at least in part, using the statistical model associated with the feature. One value for each feature can be combined to create a complex information target. The complex information target can be output.Type: GrantFiled: June 18, 2007Date of Patent: August 27, 2013Assignee: International Business Machines CorporationInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Patent number: 8285539Abstract: A method of processing text within a natural language understanding system can include applying a first tokenization technique to a sentence using a statistical tokenization model. A second tokenization technique using a named entity can be applied to the sentence when the first tokenization technique does not extract a needed token according to a class of the sentence. A token determined according to at least one of the tokenization techniques can be output.Type: GrantFiled: June 18, 2007Date of Patent: October 9, 2012Assignee: International Business Machines CorporationInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Publication number: 20080312904Abstract: A method of classifying text input for use with a natural language understanding system can include determining classification information including a primary classification and one or more secondary classifications for a received text input using a statistical classification model (statistical model). A statistical classification sub-model (statistical sub-model) can be selectively built according to a model generation criterion applied to the classification information. The method further can include selecting the primary classification or the secondary classification for the text input as a final classification according to the statistical sub-model and outputting the final classification for the text input.Type: ApplicationFiled: June 18, 2007Publication date: December 18, 2008Applicant: International Business Machines CorporationInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Publication number: 20080310718Abstract: A method of extracting information from text within a natural language understanding system can include processing a text input through at least one statistical model for each of a plurality of features to be extracted from the text input. For each feature, at least one value can be determined, at least in part, using the statistical model associated with the feature. One value for each feature can be combined to create a complex information target. The complex information target can be output.Type: ApplicationFiled: June 18, 2007Publication date: December 18, 2008Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Publication number: 20080312906Abstract: A method of creating a statistical classification model for a classifier within a natural language understanding system can include processing training data using an existing statistical classification model. Sentences of the training data correctly classified into a selected class of the statistical classification model can be selected. The selected sentences of the training data can be assigned to a fringe group or a core group according to confidence score. The training data can be updated by associating the fringe group with a fringe subclass of the selected class and the core group with a core subclass of the selected class. A new statistical classification model can be built from the updated training data. The new statistical classification model can be output.Type: ApplicationFiled: June 18, 2007Publication date: December 18, 2008Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Publication number: 20080312905Abstract: A method of processing text within a natural language understanding system can include applying a first tokenization technique to a sentence using a statistical tokenization model. A second tokenization technique using a named entity can be applied to the sentence when the first tokenization technique does not extract a needed token according to a class of the sentence. A token determined according to at least one of the tokenization techniques can be output.Type: ApplicationFiled: June 18, 2007Publication date: December 18, 2008Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy