Patents Assigned to BIOZ, INC.
  • Patent number: 11347937
    Abstract: Taught is a search engine for science tools which dynamically evaluates search rank of said science tools through Natural Language Processing and machine learning. The search engine accepts into a corpus of public and private materials, which references individual science tools. Each item of the corpus is evaluated both as to how much that given item should be trusted, and what that item says about individual science tools. Each science tool is evaluated based on what the whole corpus of input data contains concerning those science tools, taking into account how valuable the source of the data is in order to render an overall score and search rank. The search engine generates a judgement of each individual science tool, which is dynamically updated as new information becomes available in the corpus of input data.
    Type: Grant
    Filed: June 30, 2020
    Date of Patent: May 31, 2022
    Assignee: Bioz, Inc.
    Inventors: Daniel Levitt, Karin Lachmi, Dan Grunspan, Ehud Pardo
  • Patent number: 11281678
    Abstract: Taught is a search engine for science tools which dynamically evaluates search rank of said science tools through Natural Language Processing and machine learning. The search engine accepts into a corpus of public and private materials, which references individual science tools. Each item of the corpus is evaluated both as to how much that given item should be trusted, and what that item says about individual science tools. Each science tool is evaluated based on what the whole corpus of input data contains concerning those science tools, taking into account how valuable the source of the data is in order to render an overall score and search rank. The search engine generates a judgement of each individual science tool, which is dynamically updated as new information becomes available in the corpus of input data.
    Type: Grant
    Filed: January 14, 2019
    Date of Patent: March 22, 2022
    Assignee: Bioz, Inc.
    Inventors: Karin Lachmi, Daniel Levitt, Ehud Pardo, Dan Grunspan
  • Patent number: 10956427
    Abstract: Taught is a search engine for science tools which dynamically evaluates search rank of said science tools through Natural Language Processing and machine learning. The search engine accepts into a corpus of public and private materials, which references individual science tools. Each item of the corpus is evaluated both as to how much that given item should be trusted, and what that item says about individual science tools. Each science tool is evaluated based on what the whole corpus of input data contains concerning those science tools, taking into account how valuable the source of the data is in order to render an overall score and search rank. The search engine generates a judgement of each individual science tool, which is dynamically updated as new information becomes available in the corpus of input data.
    Type: Grant
    Filed: May 25, 2017
    Date of Patent: March 23, 2021
    Assignee: BIOZ, INC.
    Inventors: Karin Lachmi, Daniel Levitt, Ehud Pardo, Dan Grunspan
  • Patent number: 10796101
    Abstract: Disclosed herein are methods, systems, and apparatuses, including computer programs encoded on computer storage media, for computing numeric representations of words. One of the methods includes obtaining, from a corpus of journals, a plurality of objects. The corpus is analyzed for contextual clues as to the nature of each of these objects. Contextual analysis may include an analysis of particular fields of metadata to do with the objects. Another example of contextual analysis involves identification of an experiment that a group of objects are commonly associated with and merging objects therefrom. A third contextual analysis example makes use of word vectors about each object. Using these contextual analyses, objects are merged together with the context of search results of a search engine.
    Type: Grant
    Filed: July 15, 2019
    Date of Patent: October 6, 2020
    Assignee: Bioz, Inc.
    Inventors: Karin Lachmi, Daniel Levitt, Dan Grunspan, Ehud Pardo
  • Patent number: 10726202
    Abstract: Taught is a search engine for science tools which dynamically evaluates search rank of said science tools through Natural Language Processing and machine learning. The search engine accepts into a corpus of public and private materials, which references individual science tools. Each item of the corpus is evaluated both as to how much that given item should be trusted, and what that item says about individual science tools. Each science tool is evaluated based on what the whole corpus of input data contains concerning those science tools, taking into account how valuable the source of the data is in order to render an overall score and search rank. The search engine generates a judgement of each individual science tool, which is dynamically updated as new information becomes available in the corpus of input data.
    Type: Grant
    Filed: April 10, 2017
    Date of Patent: July 28, 2020
    Assignee: Bioz, Inc.
    Inventors: Daniel Levitt, Karin Lachmi, Dan Grunspan, Ehud Pardo
  • Patent number: 10423724
    Abstract: Disclosed herein are methods, systems, and apparatuses, including computer programs encoded on computer storage media, for computing numeric representations of words. One of the methods includes obtaining, from a corpus of journals, a plurality of objects. The corpus is analyzed for contextual clues as to the nature of each of these objects. Contextual analysis may include an analysis of particular fields of metadata to do with the objects. Another example of contextual analysis involves identification of an experiment that a group of objects are commonly associated with and merging objects therefrom. A third contextual analysis example makes use of word vectors about each object. Using these contextual analyzes, objects are merged together with the context of search results of a search engine.
    Type: Grant
    Filed: May 19, 2017
    Date of Patent: September 24, 2019
    Assignee: BIOZ, INC.
    Inventors: Karin Lachmi, Daniel Levitt, Dan Grunspan, Ehud Pardo