Patents by Inventor Swapnil Vishveshwar Hingmire
Swapnil Vishveshwar Hingmire 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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SYSTEMS AND METHODS FOR SIMILARITY ANALYSIS IN INCIDENT REPORTS USING EVENT TIMELINE REPRESENTATIONS
Publication number: 20230305549Abstract: This disclosure relates to the field of incident analysis, and, more particularly, to systems and methods for similarity analysis in incident reports using event timeline representations. Conventionally, processing of repositories of incident reports to identify similar incidents is challenging due to use of unstructured text data in describing the incident reports. Timeline representation is an important knowledge representation which captures chronological ordering of the events. The timeline representation becomes useful in process of root cause analysis as causes would temporally precede the effect. To construct event timeline representations, chronological ordering of events is required. The present disclosure provides a temporal relation identification technique to obtain a timeline representation of the events. Further, a similarity identification approach is used that makes use of neural embeddings to identify similar timeline representations and in turn, similar incident reports.Type: ApplicationFiled: February 24, 2023Publication date: September 28, 2023Applicant: Tata Consultancy Services LimitedInventors: SANGAMESHWAR SURYAKANT PATIL, NITIN VIJAYKUMAR RAMRAKHIYANI, SWAPNIL VISHVESHWAR HINGMIRE, ALOK KUMAR, HARSIMRAN BEDI, MANIDEEP JELLA, GIRISH KESHAV PALSHIKAR -
Patent number: 11488270Abstract: The present disclosure provides a system and method for recommending context and sequence aware based training set to a user. The system identifies various items and keywords of a plurality of earlier trainings of the users' interest and generates a context and sequence aware recommendation model based on the context of the identified keywords. It uses a collapsed Gibbs Sampling as in generative modelling for prior trainings. Further, it applies the context and sequence aware recommendation model on various keywords that are of users' interest. The context and sequence aware recommendation model infers a plurality of subsequent trainings based on context derived from the keywords. In addition to this, the model is generated to rank the inferred plurality of subsequent topics using a probability distribution over subsequent keywords. At the last, it recommends at least one topic to the user based on ranking of the plurality of trainings.Type: GrantFiled: December 7, 2017Date of Patent: November 1, 2022Assignee: TATA CONSULTANCY SERVICES LIMITEDInventors: Rajiv Radheyshyam Srivastava, Girish Keshav Palshikar, Swapnil Vishveshwar Hingmire, Saheb Chourasia
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Publication number: 20210304072Abstract: The online shopping is highly based on human perception on products and the human perception on products depends on semantic features of products. Conventional methods provides product recommendation based on historical data and are supervised. The present disclosure receives a set of multi-modal data. A plurality of features are extracted from the set of data at a plurality of resolution levels and the plurality of features are arranged as parallel corpus based on a category associated with each data from the set of data. Further, an abstract interaction vector is computed for each element of the set of data using the parallel corpus. Further, the set of recommendations are identified by comparing the abstract interaction vector associated with the set of data with an abstract interaction vector associated with each of a plurality of items stored in the database by utilizing a similarity metric.Type: ApplicationFiled: February 12, 2021Publication date: September 30, 2021Applicant: Tata Consultancy Services LimitedInventors: Kanika KALRA, Manasi PATWARDHAN, Shirish Subhash KARANDE, Swapnil Vishveshwar HINGMIRE, Girish Keshav PALSHIKAR
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Patent number: 10810244Abstract: The present invention relates to system and method for evaluating reviewer's ability to provide feedback. The system receives feedback given by the reviewer that includes qualitative feedback and quantitative feedback. The system performs scoring of qualitative feedback to evaluate level of noise, suggestions, appreciation, specificity and duplicate comments in the qualitative feedback. Further, the system performs scoring of quantitative feedback that includes realistic score, softness score and critical nature score. Subsequently, the scores of qualitative feedback and quantitative feedback are aggregated to provide a rank to the reviewer for the reviewer's ability to provide feedback.Type: GrantFiled: October 14, 2016Date of Patent: October 20, 2020Assignee: Tata Cunsultancy Services LimitedInventors: Manoj Madhav Apte, Sachin Sharad Pawar, Girish Keshav Palshikar, Swapnil Vishveshwar Hingmire
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Publication number: 20200242563Abstract: A recruiting person handling profiles of candidates need thorough knowledge about various technologies related to requirements posted with respect to a job opening, so as to correctly interpret and identify skill level of each candidate. Lack of knowledge of the recruiting person may result in skilled candidates not getting shortlisted and candidates having no or less relevant skills getting selected, which would affect work force of an organization the candidates are being recruited for. The disclosure herein generally relates to data processing, and, more particularly, to a method and a system for determining skill similarity by using the data processing. The system automatically identifies skills that match each other, and the recruiting person may use this information to identify and shortlist right candidates for the job. The system generates skill vectors for each skill, and by comparing skill vectors of different skills, identifies skills that are similar to each other.Type: ApplicationFiled: January 28, 2020Publication date: July 30, 2020Applicant: Tata Consultancy Services LimitedInventors: Ankita JAIN, Rajiv Radheyshyam SRIVASTAVA, Girish Keshav PALSHIKAR, Nitin Vijaykumar RAMRAKHIYANI, Swapnil Vishveshwar HINGMIRE
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Publication number: 20180158164Abstract: The present disclosure provides a system and method for recommending context and sequence aware based training set to a user. The system identifies various items and keywords of a plurality of earlier trainings of the users' interest and generates a context and sequence aware recommendation model based on the context of the identified keywords. It uses a collapsed Gibbs Sampling as in generative modelling for prior trainings. Further, it applies the context and sequence aware recommendation model on various keywords that are of users' interest. The context and sequence aware recommendation model infers a plurality of subsequent trainings based on context derived from the keywords. In addition to this, the model is generated to rank the inferred plurality of subsequent topics using a probability distribution over subsequent keywords. At the last, it recommends at least one topic to the user based on ranking of the plurality of trainings.Type: ApplicationFiled: December 7, 2017Publication date: June 7, 2018Applicant: Tata Consultancy Services LimitedInventors: Rajiv Radheyshyam SRIVASTAVA, Girish Keshav Palshikar, Swapnil Vishveshwar Hingmire, Saheb Chourasia
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Patent number: 9710520Abstract: The present subject matter relates to method(s) and system(s) to rank human profiles based on selection criteria personalized to a selector. In an embodiment, the method includes obtaining querying criteria from the selector to query a database comprising a set of human profiles. Further, a subset of human profiles is determined from the set of human profiles based on the querying criteria and a default ranking mechanism. Furthermore, a selection based ranking is obtained for the subset of human profiles. Further, based on the selection based ranking, a ranking function is determined that is indicative of a relative inclination of the selector towards the one or more implicit attributes. Such a determination is by capturing at least one implicit attribute in the ranking function from the selection based ranking. Further, the ranking function is applied to rank a fresh set of human profiles based on the ranking function.Type: GrantFiled: August 6, 2014Date of Patent: July 18, 2017Assignee: Tata Consultancy Services LimitedInventors: Rajiv Radheyshyam Srivastava, Girish Keshav Palshikar, Sangameshwar Suryakant Patil, Pragati Hiralal Dungarwal, Abhay Sodani, Sachin Pawar, Savita Suhas Bhat, Swapnil Vishveshwar Hingmire
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Publication number: 20170140043Abstract: The present invention relates to system and method for evaluating reviewer's ability to provide feedback. The system receives feedback given by the reviewer that includes qualitative feedback and quantitative feedback. The system performs scoring of qualitative feedback to evaluate level of noise, suggestions, appreciation, specificity and duplicate comments in the qualitative feedback. Further, the system performs scoring of quantitative feedback that includes realistic score, softness score and critical nature score. Subsequently, the scores of qualitative feedback and quantitative feedback are aggregated to provide a rank to the reviewer for the reviewer's ability to provide feedback.Type: ApplicationFiled: October 14, 2016Publication date: May 18, 2017Applicant: Tata Consultancy SeNices LimitedInventors: Manoj Madhav APTE, Sachin Sharad PAWAR, Girish Keshav PALSHIKAR, Swapnil Vishveshwar HINGMIRE
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Publication number: 20150112983Abstract: The present subject matter relates to method(s) and system(s) to rank human profiles based on selection criteria personalized to a selector. In an embodiment, the method includes obtaining querying criteria from the selector to query a database comprising a set of human profiles. Further, a subset of human profiles is determined from the set of human profiles based on the querying criteria and a default ranking mechanism. Furthermore, a selection based ranking is obtained for the subset of human profiles. Further, based on the selection based ranking, a ranking function is determined that is indicative of a relative inclination of the selector towards the one or more implicit attributes. Such a determination is by capturing at least one implicit attribute in the ranking function from the selection based ranking. Further, the ranking function is applied to rank a fresh set of human profiles based on the ranking function.Type: ApplicationFiled: August 6, 2014Publication date: April 23, 2015Inventors: Rajiv Radheyshyam Srivastava, Girish Keshav Palshikar, Sangameshwar Suryakant Patil, Pragati Hiralal Dungarwal, Abhay Sodani, Sachin Pawar, Savita Suhas Bhat, Swapnil Vishveshwar Hingmire