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US Patent 10108695 Multi-level clustering for associating semantic classifiers with content regions

Patent 10108695 was granted and assigned to Amazon on October, 2018 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent
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Patent attributes

Patent Applicant
Amazon
Amazon
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Current Assignee
Amazon
Amazon
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
101086950
Patent Inventor Names
Santhoshkumar Manikandasadanam Kalidasa Varier0
Anaiappan Govindan0
Kalidas Yeturu0
Date of Patent
October 23, 2018
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Patent Application Number
148168940
Date Filed
August 3, 2015
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Patent Citations Received
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US Patent 12070093 Custom garment pattern blending based on body data
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US Patent 11501477 Customizing font bounding boxes for variable fonts
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US Patent 11775354 Reducing overlay network overhead across container hosts
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US Patent 11775733 Device dependent rendering of PDF content including multiple articles and a table of contents
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US Patent 11416671 Device dependent rendering of PDF content
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US Patent 11449663 Device dependent rendering of PDF content including multiple articles and a table of contents
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US Patent 11842141 Device dependent rendering of PDF content
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US Patent 11468346 Identifying sequence headings in a document
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Patent Primary Examiner
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Pavan Mamillapalli
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Patent abstract

Digital content may be processed to determine a set of containers in the content. Each container may correspond to a particular text element of the digital content such as a line of text on a page of a digital content file. Container data indicating values of base content properties for each container may be obtained. Derived content properties may be determined from the base content properties and values of the derived content properties may be determined for each container. Multiple iterations of a clustering algorithm may be executed, where each iteration involves grouping the containers into a set of clusters by applying a particular distance function to the values of a particular set of base and/or derived properties for each container. The distance function and set of properties utilized at each iteration may be configurable to obtain clusters that can be associated with particular semantic classifiers.

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