Patents by Inventor Annervaz K.M.
Annervaz K.M. 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: 11886821Abstract: Automated response generation systems and methods are disclosed. The systems can include a deep learning model specially configured to apply inferencing techniques to redesign natural language querying systems for use over knowledge graphs. The disclosed systems and methods provide a model for inferencing referred to as a Hierarchical Recurrent Path Encoder (HRPE). An entity extraction and linking module as well as a data conversion and generation module process the content of a given query. The output is processed by the proposed model to generate inferred answers.Type: GrantFiled: April 16, 2021Date of Patent: January 30, 2024Assignee: Accenture Global Solutions LimitedInventors: Shubhashis Sengupta, Annervaz K. M., Gupta Aayushee, Sandip Sinha, Shakti Naik
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Publication number: 20220335219Abstract: Automated response generation systems and methods are disclosed. The systems can include a deep learning model specially configured to apply inferencing techniques to redesign natural language querying systems for use over knowledge graphs. The disclosed systems and methods provide a model for inferencing referred to as a Hierarchical Recurrent Path Encoder (HRPE). An entity extraction and linking module as well as a data conversion and generation module process the content of a given query. The output is processed by the proposed model to generate inferred answers.Type: ApplicationFiled: April 16, 2021Publication date: October 20, 2022Inventors: Shubhashis Sengupta, Annervaz K.M., Gupta Aayushee, Sandip Sinha, Shakti Naik
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Patent number: 11144721Abstract: A system and method for transforming unstructured text into structured form is disclosed. The system and method include converting an input word sequence (e.g., sentence) into tagged output which can be then easily be converted into a structured format. The system may include a bidirectional recurrent neural network that can generate multiple labels of individual words or phrases. In some embodiments, a customized learning loss equation involving set similarity is used to generate the multiple labels.Type: GrantFiled: May 31, 2019Date of Patent: October 12, 2021Assignee: Accenture Global Solutions LimitedInventors: Jayati Deshmukh, Annervaz K. M., Shubhashis Sengupta
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Publication number: 20200380072Abstract: A system and method for transforming unstructured text into structured form is disclosed. The system and method include converting an input word sequence (e.g., sentence) into tagged output which can be then easily be converted into a structured format. The system may include a bidirectional recurrent neural network that can generate multiple labels of individual words or phrases. In some embodiments, a customized learning loss equation involving set similarity is used to generate the multiple labels.Type: ApplicationFiled: May 31, 2019Publication date: December 3, 2020Inventors: Jayati Deshmukh, Annervaz K.M., Shubhashis Sengupta
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Patent number: 10705795Abstract: A device may receive information associated with first and second bug reports to be classified as duplicate or non-duplicate bug reports. The device may identify first and second descriptions associated with the first and second bug reports, respectively. The first and second descriptions may be different descriptions having a shared description type. The device may identify a neural network for encoding the first and second descriptions, based on the shared description type. The device may encode the first description into a first vector using the neural network, and may encode the second description into a second vector using the neural network. The device may classify the first and second bug reports as duplicate or non-duplicate bug reports based on the first vector and the second vector. The device may perform an action based on classifying the first and second bug reports as duplicate or non-duplicate bug reports.Type: GrantFiled: December 18, 2017Date of Patent: July 7, 2020Assignee: Accenture Global Solutions LimitedInventors: Sanjay Podder, Jayati Deshmukh, Annervaz K M, Shubhashis Sengupta, Neville Dubash
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Publication number: 20180173495Abstract: A device may receive information associated with first and second bug reports to be classified as duplicate or non-duplicate bug reports. The device may identify first and second descriptions associated with the first and second bug reports, respectively. The first and second descriptions may be different descriptions having a shared description type. The device may identify a neural network for encoding the first and second descriptions, based on the shared description type. The device may encode the first description into a first vector using the neural network, and may encode the second description into a second vector using the neural network. The device may classify the first and second bug reports as duplicate or non-duplicate bug reports based on the first vector and the second vector. The device may perform an action based on classifying the first and second bug reports as duplicate or non-duplicate bug reports.Type: ApplicationFiled: December 18, 2017Publication date: June 21, 2018Inventors: Sanjay Podder, Jayati Deshmukh, Annervaz K M, Shubhashis Sengupta, Neville Dubash
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Patent number: 9836301Abstract: A method for component discovery from source code may include receiving source code, and determining business classes by excluding packages and classes in the source code identified as belonging to a presentation layer, as belonging to a data access layer, as models and/or as utilities. The method may further include extracting multi-dimensional features from the business classes, estimating similarity for business class pairs based on the extracted multi-dimensional features, clustering the business classes based on the similarity and mapping functional concepts to the clusters. The clusters generated by the clustering may represent components of the source code. The method may also include determining interfaces for the components based on the clustering.Type: GrantFiled: March 21, 2016Date of Patent: December 5, 2017Assignee: ACCENTURE GLOBAL SERVICES LIMITEDInventors: Janardan Misra, Annervaz K. M., Vikrant Shyamkant Kaulgud, Shubhashis Sengupta, Gary Titus
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Publication number: 20160202967Abstract: A method for component discovery from source code may include receiving source code, and determining business classes by excluding packages and classes in the source code identified as belonging to a presentation layer, as belonging to a data access layer, as models and/or as utilities. The method may further include extracting multi-dimensional features from the business classes, estimating similarity for business class pairs based on the extracted multi-dimensional features, clustering the business classes based on the similarity and mapping functional concepts to the clusters. The clusters generated by the clustering may represent components of the source code. The method may also include determining interfaces for the components based on the clustering.Type: ApplicationFiled: March 21, 2016Publication date: July 14, 2016Applicant: Accenture Global Services LimitedInventors: Janardan MISRA, Annervaz K.M., Vikrant Shyamkant KAULGUD, Shubhashis SENGUPTA, Gary TITUS
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Patent number: 9323520Abstract: A method for component discovery from source code may include receiving source code, and determining business classes by excluding packages and classes in the source code identified as belonging to a presentation layer, as belonging to a data access layer, as models and/or as utilities. The method may further include extracting multi-dimensional features from the business classes, estimating similarity for business class pairs based on the extracted multi-dimensional features, clustering the business classes based on the similarity and mapping functional concepts to the clusters. The clusters generated by the clustering may represent components of the source code. The method may also include determining interfaces for the components based on the clustering.Type: GrantFiled: October 1, 2014Date of Patent: April 26, 2016Assignee: ACCENTURE GLOBAL SERVICES LIMITEDInventors: Janardan Misra, Annervaz K. M., Vikrant Shyamkant Kaulgud, Shubhashis Sengupta, Gary Titus
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Publication number: 20150020048Abstract: A method for component discovery from source code may include receiving source code, and determining business classes by excluding packages and classes in the source code identified as belonging to a presentation layer, as belonging to a data access layer, as models and/or as utilities. The method may further include extracting multi-dimensional features from the business classes, estimating similarity for business class pairs based on the extracted multi-dimensional features, clustering the business classes based on the similarity and mapping functional concepts to the clusters. The clusters generated by the clustering may represent components of the source code. The method may also include determining interfaces for the components based on the clustering.Type: ApplicationFiled: October 1, 2014Publication date: January 15, 2015Inventors: Janardan MISRA, Annervaz K.M., Vikrant Shyamkant KAULGUD, Shubhashis SENGUPTA, Gary TITUS
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Publication number: 20130268916Abstract: A method for component discovery from source code may include receiving source code, and determining business classes by excluding packages and classes in the source code identified as belonging to a presentation layer, as belonging to a data access layer, as models and/or as utilities. The method may further include extracting multi-dimensional features from the business classes, estimating similarity for business class pairs based on the extracted multi-dimensional features, clustering the business classes based on the similarity and mapping functional concepts to the clusters. The clusters generated by the clustering may represent components of the source code. The method may also include determining interfaces for the components based on the clustering.Type: ApplicationFiled: June 12, 2012Publication date: October 10, 2013Applicant: Accenture Global Services LimitedInventors: Janardan MISRA, Annervaz K.M., Vikrant Shyamkant Kaulgud, Shubhashis Sengupta, Gary Titus