Patents by Inventor Sameep Navin Solanki

Sameep Navin Solanki 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: 11275746
    Abstract: The present disclosure is directed to apparatuses, systems, and methods for enhancing search results based on recent user interactions. As described herein, embodiments may infer various refinements for search queries; these refinements are based, at least in part, on the user's recent interactions with the search platform (e.g., within a current session). In other words, as the user is interacting with the search platform, one or more refinements may be inferred to help make the search results more relevant to the user.
    Type: Grant
    Filed: August 5, 2019
    Date of Patent: March 15, 2022
    Assignee: eBay Inc.
    Inventors: Sameep Navin Solanki, Jayasimha Katukuri, Manas Haribhai Somaiya, Rajyashree Mukherjee, Rakesh Setty
  • Publication number: 20210056265
    Abstract: In various example embodiments, a system and method for a Target Language Engine are presented. The Target Language Engine augments a synonym list in a base dictionary of a target language with one or more historical search queries previously submitted to search one or more listings in listing data. The Target Language Engine identifies a compound word and a plurality of words present in the listing data that have a common meaning in the target language. Each word from the plurality of words is present in the compound word. The Target Language Engine causes a database to create an associative link between the portion of text and a word selected from at least one of the synonym list or the plurality of words.
    Type: Application
    Filed: November 9, 2020
    Publication date: February 25, 2021
    Inventors: Chandra Prakash Khatri, Selcuk Kopru, Nish Parikh, Justin Nicholas House, Sameep Navin Solanki
  • Publication number: 20200320370
    Abstract: Systems, methods and media are provided for training a snippet extractor to create snippets based on information extracted from published descriptions. In one example, a computer-implemented method includes creating, based on a non-RNN (Recurrent Neural Network) extraction technique performed on the published descriptions, a plurality of base models, each base model including one or more sample description summaries; evaluating the base models using an evaluation technique; selecting an optimum base model; developing a classification model using RNN extraction, the classification model based on description summaries contained in the optimum base model; and using the classification model to train the snippet extractor by machine learning.
    Type: Application
    Filed: April 24, 2020
    Publication date: October 8, 2020
    Inventors: Chandra Prakash Khatri, Nish Parikh, Sameep Navin Solanki, Justin Nicholas House, Gyanit Singh
  • Publication number: 20200117855
    Abstract: In various example embodiments, a system and method for a Target Language Engine are presented. The Target Language Engine augments a synonym list in a base dictionary of a target language with one or more historical search queries previously submitted to search one or more listings in listing data. The Target Language Engine identifies a compound word and a plurality of words present in the listing data that have a common meaning in the target language. Each word from the plurality of words is present in the compound word. The Target Language Engine causes a database to create an associative link between the portion of text and a word selected from at least one of the synonym list or the plurality of words.
    Type: Application
    Filed: August 21, 2019
    Publication date: April 16, 2020
    Inventors: Chandra Prakash Khatri, Selcuk Kopru, Nish Parikh, Justin Nicholas House, Sameep Navin Solanki
  • Patent number: 10521509
    Abstract: In various example embodiments, a system and method for a Target Language Engine are presented. The Target Language Engine augments a synonym list in a base dictionary of a target language with one or more historical search queries previously submitted to search one or more listings in listing data. The Target Language Engine identifies a compound word and a plurality of words present in the listing data that have a common meaning in the target language. Each word from the plurality of words is present in the compound word. The Target Language Engine causes a database to create an associative link between the portion of text and a word selected from at least one of the synonym list or the plurality of words.
    Type: Grant
    Filed: August 15, 2016
    Date of Patent: December 31, 2019
    Assignee: eBay Inc.
    Inventors: Chandra Prakash Khatri, Selcuk Kopru, Nish Parikh, Justin Nicholas House, Sameep Navin Solanki
  • Patent number: 10489407
    Abstract: The present disclosure is directed to apparatuses, systems, and methods for enhancing search results based on recent user interactions. As described herein, embodiments may infer various refinements for search queries; these refinements are based, at least in part, on the user's recent interactions with the search platform (e.g., within a current session). In other words, as the user is interacting with the search platform, one or more refinements may be inferred to help make the search results more relevant to the user.
    Type: Grant
    Filed: May 20, 2015
    Date of Patent: November 26, 2019
    Assignee: EBAY INC.
    Inventors: Sameep Navin Solanki, Jayasimha Katukuri, Manas Haribhai Somaiya, Rajyashree Mukherjee, Rakesh Setty
  • Publication number: 20190354532
    Abstract: The present disclosure is directed to apparatuses, systems, and methods for enhancing search results based on recent user interactions. As described herein, embodiments may infer various refinements for search queries; these refinements are based, at least in part, on the user's recent interactions with the search platform (e.g., within a current session). In other words, as the user is interacting with the search platform, one or more refinements may be inferred to help make the search results more relevant to the user.
    Type: Application
    Filed: August 5, 2019
    Publication date: November 21, 2019
    Inventors: Sameep Navin Solanki, Jayasimha Katukuri, Manas Haribhai Somaiya, Rajyashree Mukherjee, Rakesh Setty
  • Publication number: 20180046611
    Abstract: In various example embodiments, a system and method for a Target Language Engine are presented. The Target Language Engine augments a synonym list in a base dictionary of a target language with one or more historical search queries previously submitted to search one or more listings in listing data. The Target Language Engine identifies a compound word and a plurality of words present in the listing data that have a common meaning in the target language. Each word from the plurality of words is present in the compound word. The Target Language Engine causes a database to create an associative link between the portion of text and a word selected from at least one of the synonym list or the plurality of words.
    Type: Application
    Filed: August 15, 2016
    Publication date: February 15, 2018
    Inventors: Chandra Prakash Khatri, Selcuk Kopru, Nish Parikh, Justin Nicholas House, Sameep Navin Solanki
  • Publication number: 20170213130
    Abstract: Systems, methods and media are provided for training a snippet extractor to create snippets based on information extracted from published descriptions. In one example, a computer-implemented method includes creating, based on a non-RNN (Recurrent Neural Network) extraction technique performed on the published descriptions, a plurality of base models, each base model including one or more sample description summaries; evaluating the base models using an evaluation technique; selecting an optimum base model; developing a classification model using RNN extraction, the classification model based on description summaries contained in the optimum base model; and using the classification model to train the snippet extractor by machine learning.
    Type: Application
    Filed: September 16, 2016
    Publication date: July 27, 2017
    Inventors: Chandra Prakash Khatri, Nish Parikh, Sameep Navin Solanki, Justin Nicholas House, Gyanit Singh
  • Publication number: 20160078038
    Abstract: Systems and methods are presented for generating snippets from document data within the document and category taxonomies. In some embodiments, the system may receive a document comprising a set of paragraphs and sentences, identify text in the document relating to a set of categories, and score the paragraphs based on a relation between the paragraph and the set of categories to produce a section score. The system determines one or more sentences for inclusion in a snippet based in part on the section score. The system generates a snippet from the sentences determined for inclusion and associates the snippet with the document.
    Type: Application
    Filed: September 11, 2015
    Publication date: March 17, 2016
    Inventors: Sameep Navin Solanki, Jagadish Nallapaneni, Tracy Holloway King, Naren Chittar
  • Patent number: 8515980
    Abstract: Described herein are methods and systems for promoting item listings that satisfy a query based on the item listings being assigned to certain categories that have, based on historical click data, exhibited high demand characteristics for the query. Consistent with some embodiments, a certain number of leaf-level categories are identified based on demand data for those categories, and the item listings assigned to those categories are promoted through a weighting factor derived in part based on the click probability score associated with the category. In some embodiments, certain sub-categories may be selected when the demand associated with the child categories of the sub-category is well balanced.
    Type: Grant
    Filed: July 16, 2010
    Date of Patent: August 20, 2013
    Assignee: eBay Inc.
    Inventors: Michael Mathieson, Sanjay Pundlkrao Ghatare, Vipul C. Dalal, Sameep Navin Solanki, Muhammad Faisal Rehman
  • Publication number: 20120016873
    Abstract: Described herein are methods and systems for promoting item listings that satisfy a query based on the item listings being assigned to certain categories that have, based on historical click data, exhibited high demand characteristics for the query. Consistent with some embodiments, a certain number of leaf-level categories are identified based on demand data for those categories, and the item listings assigned to those categories are promoted through a weighting factor derived in part based on the click probability score associated with the category. In some embodiments, certain sub-categories may be selected when the demand associated with the child categories of the sub-category is well balanced.
    Type: Application
    Filed: July 16, 2010
    Publication date: January 19, 2012
    Inventors: Michael Mathieson, Sanjay Pundlkrao Ghatare, Vipul C. Dalal, Sameep Navin Solanki, Muhammad Faisal Rehman