Patents by Inventor Lakshman Shyam Sundar Maddali

Lakshman Shyam Sundar Maddali 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: 11893627
    Abstract: In various exemplary embodiments, a system and associated method to perform an adaptive risk-based assessment of a user is disclosed. A method includes receiving a request from a user to perform an action at an electronic marketplace, retrieving a plurality of risk assessment factors associated with the action and the user, performing a risk assessment process on the risk assessment factors to identify a risk mitigation process, requesting that the user perform the identified risk mitigation process, and allowing the user to perform the action in response to the user completing the risk mitigation.
    Type: Grant
    Filed: September 5, 2019
    Date of Patent: February 6, 2024
    Assignee: EBAY INC.
    Inventors: Farhang Kassaei, Amanda A. Earhart, Snezana Sahter, Srinivasu Gottipati, Lars Wright, Craig Rowley, Lakshman Shyam Sundar Maddali, Nainesh Nayudu
  • Publication number: 20190392514
    Abstract: In various exemplary embodiments, a system and associated method to perform an adaptive risk-based assessment of a user is disclosed. A method includes receiving a request from a user to perform an action at an electronic marketplace, retrieving a plurality of risk assessment factors associated with the action and the user, performing a risk assessment process on the risk assessment factors to identify a risk mitigation process, requesting that the user perform the identified risk mitigation process, and allowing the user to perform the action in response to the user completing the risk mitigation.
    Type: Application
    Filed: September 5, 2019
    Publication date: December 26, 2019
    Inventors: Farhang Kassaei, Amanda A. Earhart, Snezana Sahter, Srinivasu Gottipati, Lars Wright, Craig Rowley, Lakshman Shyam Sundar Maddali, Nainesh Nayudu
  • Patent number: 10489853
    Abstract: In various exemplary embodiments, a system and associated method to perform an adaptive risk-based assessment of a user is disclosed. A method includes receiving a request from a user to perform an action at an electronic marketplace, retrieving a plurality of risk assessment factors associated with the action and the user, performing a risk assessment process on the risk assessment factors to identify a risk mitigation process, requesting that the user perform the identified risk mitigation process, and allowing the user to perform the action in response to the user completing the risk mitigation.
    Type: Grant
    Filed: November 20, 2017
    Date of Patent: November 26, 2019
    Assignee: eBay Inc.
    Inventors: Farhang Kassaei, Amanda A. Earhart, Snezana Sahter, Srinivasu Gottipati, Lars Wright, Craig Rowley, Lakshman Shyam Sundar Maddali, Nainesh Nayudu
  • Publication number: 20180082364
    Abstract: In various exemplary embodiments, a system and associated method to perform an adaptive risk-based assessment of a user is disclosed. The method includes assigning a risk assessment process to the user and providing a plurality of assessment factors to the risk assessment process. The plurality of assessment factors are based on both the user (e.g., previously assessed factors, residence, phone number, address, etc.) and one or more actions the user may perform (e.g., selling an item in an electronic marketplace and the value of the item). A post-action analysis of the risk assessment process is performed. The risk assessment process can be modified based on a determination of the post-action analysis.
    Type: Application
    Filed: November 20, 2017
    Publication date: March 22, 2018
    Inventors: Farhang Kassaei, Amanda A. Earhart, Snezana Sahter, Srinivasu Gottipati, Lars Wright, Craig Rowley, Lakshman Shyam Sundar Maddali, Nainesh Nayudu
  • Patent number: 9830643
    Abstract: In various exemplary embodiments, a system and associated method to perform an adaptive risk-based assessment of a user is disclosed. The method includes assigning a risk assessment process to the user and providing a plurality of assessment factors to the risk assessment process. The plurality of assessment factors are based on both the user (e.g., previously assessed factors, residence, phone number, address, etc.) and one or more actions the user may perform (e.g., selling an item in an electronic marketplace and the value of the item). A post-action analysis of the risk assessment process is performed. The risk assessment process can be modified based on a determination of the post-action analysis.
    Type: Grant
    Filed: June 12, 2009
    Date of Patent: November 28, 2017
    Assignee: eBay Inc.
    Inventors: Farhang Kassaei, Amanda A. Earhart, Snezana Sahter, Srinivasu Gottipati, Lars Wright, Craig Rowley, Lakshman Shyam Sundar Maddali, Nainesh Nayudu
  • Patent number: 9779428
    Abstract: Reconciling detailed transaction feedback by detecting a rating of a transaction, where the rating indicates a negative experience, mining the sentiment of words in feedback text that is included with or as part of the rating to detect whether the words indicate positive sentiment or negative sentiment, responsive to determining that the words in the feedback text indicate that the feedback text connotes a positive sentiment, adjusting the rating of the transaction. The mining may include testing words in the feedback text to detect whether the words indicate positive sentiment or negative sentiment by calculating a sentiment score.
    Type: Grant
    Filed: October 19, 2016
    Date of Patent: October 3, 2017
    Assignee: eBay Inc.
    Inventors: Lakshman Shyam Sundar Maddali, Avani Goel Sharma
  • Publication number: 20170039606
    Abstract: Reconciling detailed transaction feedback by detecting a rating of a transaction, where the rating indicates a negative experience, mining the sentiment of words in feedback text that is included with or as part of the rating to detect whether the words indicate positive sentiment or negative sentiment, responsive to determining that the words in the feedback text indicate that the feedback text connotes a positive sentiment, adjusting the rating of the transaction. The mining may include testing words in the feedback text to detect whether the words indicate positive sentiment or negative sentiment by calculating a sentiment score.
    Type: Application
    Filed: October 19, 2016
    Publication date: February 9, 2017
    Inventors: Lakshman Shyam Sundar Maddali, Avani Goel Sharma
  • Patent number: 9495695
    Abstract: Reconciling detailed transaction feedback by detecting a rating of a transaction, where the rating indicates a negative experience, mining the sentiment of words in feedback text that is included with or as part of the rating to detect whether the words indicate positive sentiment or negative sentiment, responsive to determining that the words in the feedback text indicate that the feedback text connotes a positive sentiment, adjusting the rating of the transaction. The mining may include testing words in the feedback text to detect whether the words indicate positive sentiment or negative sentiment by calculating a sentiment score.
    Type: Grant
    Filed: March 31, 2016
    Date of Patent: November 15, 2016
    Assignee: eBay Inc.
    Inventors: Lakshman Shyam Sundar Maddali, Avani Goel Sharma
  • Publication number: 20160210673
    Abstract: Reconciling detailed transaction feedback by detecting a rating of a transaction, where the rating indicates a negative experience, mining the sentiment of words in feedback text that is included with or as part of the rating to detect whether the words indicate positive sentiment or negative sentiment, responsive to determining that the words in the feedback text indicate that the feedback text connotes a positive sentiment, adjusting the rating of the transaction. The mining may include testing words in the feedback text to detect whether the words indicate positive sentiment or negative sentiment by calculating a sentiment score.
    Type: Application
    Filed: March 31, 2016
    Publication date: July 21, 2016
    Inventors: Lakshman Shyam Sundar Maddali, Avani Goel Sharma
  • Patent number: 9342846
    Abstract: Reconciling detailed transaction feedback by detecting a rating of a transaction, where the rating indicates a negative experience, mining the sentiment of words in feedback text that is included with or as part of the rating to detect whether the words indicate positive sentiment or negative sentiment, responsive to determining that the words in the feedback text indicate that the feedback text connotes a positive sentiment, adjusting the rating of the transaction. The mining may include testing words in the feedback text to detect whether the words indicate positive sentiment or negative sentiment by calculating a sentiment score.
    Type: Grant
    Filed: April 12, 2013
    Date of Patent: May 17, 2016
    Assignee: eBay Inc.
    Inventors: Lakshman Shyam Sundar Maddali, Avani Goel Sharma
  • Publication number: 20140309987
    Abstract: Reconciling detailed transaction feedback by detecting a rating of a transaction, where the rating indicates a negative experience, mining the sentiment of words in feedback text that is included with or as part of the rating to detect whether the words indicate positive sentiment or negative sentiment, responsive to determining that the words in the feedback text indicate that the feedback text connotes a positive sentiment, adjusting the rating of the transaction. The mining may include testing words in the feedback text to detect whether the words indicate positive sentiment or negative sentiment by calculating a sentiment score.
    Type: Application
    Filed: April 12, 2013
    Publication date: October 16, 2014
    Applicant: eBay Inc.
    Inventors: Lakshman Shyam Sundar Maddali, Avani Goel Sharma
  • Patent number: 7930260
    Abstract: A method for near real time patterns identification, in one example embodiment, comprises receiving a data stream containing information associated with a transaction and participants of the transaction and receiving an Artificial Intelligence (AI) algorithm trained to score data in the data stream. The method may further comprise receiving metadata associated with the historical information, comparing the data stream to the metadata by measuring differences between variables included in the historical metadata and the data stream. The method may further comprise modifying the data stream to suit the AI algorithm when the differences between variables are below predetermined threshold values and retraining the AI algorithm based on the data stream when the differences between the variables are greater than the predetermined threshold values. The method may further comprise feeding the data stream to the AI algorithm to classify the variables in the data stream.
    Type: Grant
    Filed: February 14, 2008
    Date of Patent: April 19, 2011
    Assignee: eBay Inc.
    Inventors: Harshal Ulhas Deo, Brian Matthew Carnes, Lakshman Shyam Sundar Maddali
  • Publication number: 20100250387
    Abstract: In various exemplary embodiments, a system and associated method to perform an adaptive risk-based assessment of a user is disclosed. The method includes assigning a risk assessment process to the user and providing a plurality of assessment factors to the risk assessment process. The plurality of assessment factors are based on both the user (e.g., previously assessed factors, residence, phone number, address, etc.) and one or more actions the user may perform (e.g., selling an item in an electronic marketplace and the value of the item). A post-action analysis of the risk assessment process is performed. The risk assessment process can be modified based on a determination of the post-action analysis.
    Type: Application
    Filed: June 12, 2009
    Publication date: September 30, 2010
    Inventors: Farhang Kassaei, Amanda A. Earhart, Snezana Sahter, Srinivasu Gottipati, Lars Wright, Craig Rowley, Lakshman Shyam Sundar Maddali, Nainesh Nayudu