Patents by Inventor Krishna Sravanthi

Krishna Sravanthi 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: 12147420
    Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and execute functions comprising: storing historical session data pertaining to user sessions and archived search queries submitted by users to a search engine; analyzing the historical session data to identify ambiguous queries, including semantically ambiguous queries and multi-language queries; monitoring search queries submitted to the search engine to detect the ambiguous queries; and in response to detecting an ambiguous query, generating a query resolution interface that displays categorical groupings, each of which corresponds to a possible intention of the ambiguous query. Other embodiments are disclosed herein.
    Type: Grant
    Filed: January 31, 2022
    Date of Patent: November 19, 2024
    Assignee: WALMART APOLLO, LLC
    Inventors: Leonardo Lezcano, Vachik Shailesh, Krishna Sravanthi, Ciya Liao, Pankaj Adsul, Rajyashree Mukherjee
  • Publication number: 20240256532
    Abstract: A method can include determining, via a translatability classifier module, a translatability class label for a cross-lingual search query received, via a computer network, from a user device for a user. The translatability classifier module can be trained to determine the translatability class label among multiple translatability class labels associated with user intentions for the cross-lingual search query based on a respective probability of the cross-lingual search query being associated with each of the multiple translatability class labels. The method further can include determining, via a language translator module, a class-associated search query for the cross-lingual search query based on the translatability class label, as determined. The method additionally can include transmitting, via the computer network, the class-associated search query to a monolingual search engine. Other embodiments are disclosed.
    Type: Application
    Filed: January 31, 2023
    Publication date: August 1, 2024
    Applicant: Walmart Apollo, LLC
    Inventors: Leonardo Lezcano, Pankaj Appasaheb Adsul, Jesus Perez Martin, Jorge Gomez Robles, Krishna Sravanthi Rajanala Sai, Ciya Liao
  • Publication number: 20240256587
    Abstract: A method can include determining a translatability class label and a class-associated search query for a cross-lingual search query. Determining the translatability class label and the class-associated search query can include determining whether a first class-translation pair for the cross-lingual search query exists in a memory module. If the first class-translation pair exists in the memory module, the method further can include retrieving the first class-translation pair for the cross-lingual search query from the memory module. When no class-translation pair for the cross-lingual search query exists in the memory module, the method additionally can include: determining the translatability class label, and determining the class-associated search query based on the translatability class label.
    Type: Application
    Filed: January 31, 2023
    Publication date: August 1, 2024
    Applicant: Walmart Apollo, LLC
    Inventors: Leonardo Lezcano, Pankaj Appasaheb Adsul, Jesus Perez Martin, Jorge Gomez Robles, Krishna Sravanthi Rajanala Sai, Ciya Liao
  • Publication number: 20230281194
    Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and execute functions comprising: storing historical session data pertaining to user sessions and archived search queries submitted by users to a search engine; analyzing the historical session data to identify ambiguous queries, including semantically ambiguous queries and multi-language queries; monitoring search queries submitted to the search engine to detect the ambiguous queries; and in response to detecting an ambiguous query, generating a query resolution interface that displays categorical groupings, each of which corresponds to a possible intention of the ambiguous query. Other embodiments are disclosed herein.
    Type: Application
    Filed: January 31, 2022
    Publication date: September 7, 2023
    Applicant: Walmart Apollo, LLC
    Inventors: Leonardo Lezcano, Vachik Shailesh, Krishna Sravanthi, Ciya Liao, Pankaj Adsul, Rajyashree Mukherjee
  • Patent number: 11200269
    Abstract: Examples of the present disclosure describe systems and methods relating to generating relevance scores for one or more words of a passage which is an answer to a natural language query. For instance, a passage extracted from a highly relevant electronic file along with the query may encoded and augmented to generate a multi-dimensional, augmented semantic vectors using recurring neural networks. The augmented semantic vectors along with a multi-dimensional vector that represent words of the passage may be decoded to generate relevance scores for one or more words of the passage, based on levels of relevance to the query.
    Type: Grant
    Filed: June 15, 2017
    Date of Patent: December 14, 2021
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Qifa Ke, Frank Torsten Bernd Seide, Qi Liu, Rajanala Sai Krishna Sravanthi
  • Patent number: 10169453
    Abstract: A summary of a document is generated in near real time. In aspects, an indication to summarize the document is received and the document is processed to generate a summary. For instance, processing includes extracting sentences from the document and generating a plurality of candidate passages from the extracted sentences. Features are extracted from each of the plurality of candidate passages and each candidate passage is ranked based at least in part on the extracted features. High-ranking candidate passages are considered likely to be important and/or representative of the document. A summary of the document is generated including one or more of the high-ranking candidate passages. The summary includes portions of the document that are considered important and/or representative of the document, so a user may review the summary in lieu of reading the entire document.
    Type: Grant
    Filed: March 28, 2016
    Date of Patent: January 1, 2019
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Gang Luo, Qi Liu, Krishna Sravanthi Rajanala Sai, Dario Bigongiari, Qifa Ke, Oana Diana Nicolov, Srinivas Vadrevu
  • Publication number: 20180365321
    Abstract: Examples of the present disclosure describe systems and methods relating to generating relevance scores for one or more words of a passage which is an answer to a natural language query. For instance, a passage extracted from a highly relevant electronic file along with the query may encoded and augmented to generate a multi-dimensional, augmented semantic vectors using recurring neural networks. The augmented semantic vectors along with a multi-dimensional vector that represent words of the passage may be decoded to generate relevance scores for one or more words of the passage, based on levels of relevance to the query.
    Type: Application
    Filed: June 15, 2017
    Publication date: December 20, 2018
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Qifa KE, Frank Torsten Bernd SEIDE, Qi LIU, Rajanala Sai Krishna SRAVANTHI
  • Publication number: 20170277668
    Abstract: A summary of a document is generated in near real time. In aspects, an indication to summarize the document is received and the document is processed to generate a summary. For instance, processing includes extracting sentences from the document and generating a plurality of candidate passages from the extracted sentences. Features are extracted from each of the plurality of candidate passages and each candidate passage is ranked based at least in part on the extracted features. High-ranking candidate passages are considered likely to be important and/or representative of the document. A summary of the document is generated including one or more of the high-ranking candidate passages. The summary includes portions of the document that are considered important and/or representative of the document, so a user may review the summary in lieu of reading the entire document.
    Type: Application
    Filed: March 28, 2016
    Publication date: September 28, 2017
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Gang Luo, Qi Liu, Krishna Sravanthi Rajanala Sai, Dario Bigongiari, Qifa Ke, Oana Diana Nicolov, Srinivas Vadrevu