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US Patent 10229148 Multi-language support for interfacing with distributed data

Patent 10229148 was granted and assigned to Arimo (company) on March, 2019 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
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Patent attributes

Patent Applicant
Arimo (company)
Arimo (company)
0
Current Assignee
Arimo (company)
Arimo (company)
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
102291480
Patent Inventor Names
Christopher T. Nguyen0
Anh H. Trinh0
Bach D. Bui0
Date of Patent
March 12, 2019
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Patent Application Number
148144570
Date Filed
July 30, 2015
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Patent Citations Received
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US Patent 11488602 Meeting transcription using custom lexicons based on document history
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US Patent D898060 Display screen or portion thereof with graphical user interface
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US Patent 10795935 Automated generation of job flow definitions
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US Patent 10943060 Automated outline generation of captured meeting audio in a collaborative document context
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US Patent 11275891 Automated outline generation of captured meeting audio in a collaborative document context
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US Patent 11656917 Distributed processing management apparatus, distributed processing method, and computer-readable recording medium
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US Patent 11689379 Generating customized meeting insights based on user interactions and meeting media
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US Patent 10503498 Scalable cloud-based time series analysis
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Patent Primary Examiner
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Rehana Perveen
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Patent abstract

A data analysis system stores in-memory representation of a distributed data structure across a plurality of processors of a parallel or distributed system. Client applications interact with the in-memory distributed data structure to process queries using the in-memory distributed data structure and to modify the in-memory distributed data structure. The data analysis system creates uniform resource identifier (URI) to identify each in-memory distributed data structure. The URI can be communicated from one client application to another application using communication mechanisms outside the data analysis system, for example, by email, thereby allowing other client devices to interact with a particular in-memory distributed data structure. The in-memory distributed data structure can be a machine learning model that is trained by one client device and executed by another client device. A client application can interact with the in-memory distributed data structure using different programming languages.

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