发明申请
US20160162458A1 GRAPHICAL SYSTEMS AND METHODS FOR HUMAN-IN-THE-LOOP MACHINE INTELLIGENCE
审中-公开
人造环境机器智能的图形系统和方法
- 专利标题: GRAPHICAL SYSTEMS AND METHODS FOR HUMAN-IN-THE-LOOP MACHINE INTELLIGENCE
- 专利标题(中): 人造环境机器智能的图形系统和方法
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申请号: US14964522申请日: 2015-12-09
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公开(公告)号: US20160162458A1公开(公告)日: 2016-06-09
- 发明人: Robert J. Munro , Christopher Walker , Sarah K. Luger , Jason Brenier , Paul A. Tepper , Ross Mechanic , Andrew Gilchrist-Scott , Gary C. King , Brendan D. Callahan , Tyler J. Schnoebelen , Edgar Nunez , Haley Most
- 申请人: Robert J. Munro , Christopher Walker , Sarah K. Luger , Jason Brenier , Paul A. Tepper , Ross Mechanic , Andrew Gilchrist-Scott , Gary C. King , Brendan D. Callahan , Tyler J. Schnoebelen , Edgar Nunez , Haley Most
- 申请人地址: US CA San Francisco
- 专利权人: Idibon, Inc.
- 当前专利权人: Idibon, Inc.
- 当前专利权人地址: US CA San Francisco
- 主分类号: G06F17/24
- IPC分类号: G06F17/24 ; G06F3/0482
摘要:
Methods and systems are disclosed for creating and linking a series of interfaces configured to display information and receive confirmation of classifications made by a natural language modeling engine to improve organization of a collection of documents into an hierarchical structure. In some embodiments, the interfaces may display to an annotator a plurality of labels of potential classifications for a document as identified by a natural language modeling engine, collect annotated responses from the annotator, aggregate the annotated responses across other annotators, analyze the accuracy of the natural language modeling engine based on the aggregated annotated responses, and predict accuracies of the natural language modeling engine's classifications of the documents.
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