Invention Grant
- Patent Title: Learning the structure of hierarchical extraction models
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Application No.: US15798282Application Date: 2017-10-30
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Publication No.: US11295232B2Publication Date: 2022-04-05
- Inventor: David Maxwell Chickering
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: Microsoft Technology Licensing, LLC
- Current Assignee: Microsoft Technology Licensing, LLC
- Current Assignee Address: US WA Redmond
- Agency: Schwegman Lundberg & Woessner, P.A.
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06F16/30

Abstract:
A hierarchical extraction model for a label hierarchy may be implemented by a weighted hierarchical state machine whose structure and/or weights are determined in part from a statistical distribution of label sequences as determined from training data. In accordance with various embodiments, the hierarchical state machine includes one or more non-cyclic directed chains of states representing at least a subset of the label sequences, and transitions weighted based at least in part on the statistical distribution.
Public/Granted literature
- US20190130308A1 LEARNING THE STRUCTURE OF HIERARCHICAL EXTRACTION MODELS Public/Granted day:2019-05-02
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