Patents by Inventor Krishna Sravanthi Rajanala Sai

Krishna Sravanthi Rajanala Sai 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).

  • 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
  • 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: 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