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CLASSIFICATION MODEL LEARNING DEVICE, CLASSIFICATION MODEL LEARNING METHOD, AND PROGRAM FOR LEARNING CLASSIFICATION MODEL

机译:分类模型学习装置,分类模型学习方法以及学习分类模型的程序

摘要

PPROBLEM TO BE SOLVED: To provide a technique for learning a classification model for sorting an appropriate learning instance from generated learning instances and accurately identifying whether it contains an event or not. PSOLUTION: The classification model learning device for learning a classification model for extracting, based on a plurality of learning texts each including a text and presence/absence information of a specific event, the specific event from a text determined for the presence/absence of the specific event comprises: an event relevant expression determination part 30 applying an event relevant expression for determining the presence/absence of the specific event to each of the plurality of learning texts to determine the presence/absence of the specific event in the learning text concerned; a learning text extraction part 40 extracting a learning text according to the presence/absence of the specific event determined by the event relevant expression determination part; and a classification model learning part 50 learning the classification model based on the learning text extracted by the learning text extraction part. PCOPYRIGHT: (C)2007,JPO&INPIT
机译:

要解决的问题:提供一种用于学习分类模型的技术,该分类模型用于从生成的学习实例中对适当的学习实例进行排序,并准确地识别其中是否包含事件。

解决方案:分类模型学习设备,用于学习分类模型,该分类模型用于基于多个学习文本,每个学习文本包括文本和特定事件的存在/不存在信息,从针对存在/确定的文本中提取特定事件。特定事件的不存在包括:事件相关表达确定部分30将用于确定特定事件的存在/不存在的事件相关表达应用于多个学习文本中的每一个,以确定学习中特定事件的存在/不存在。有关文本;学习文本提取部分40根据由事件相关表达确定部分确定的特定事件的存在/不存在来提取学习文本;分类模型学习部分50基于由学习文本提取部分提取的学习文本来学习分类模型。

版权:(C)2007,日本特许厅&INPIT

著录项

  • 公开/公告号JP2007157058A

    专利类型

  • 公开/公告日2007-06-21

    原文格式PDF

  • 申请/专利权人 TOSHIBA CORP;

    申请/专利号JP20050354939

  • 发明设计人 SAKURAI SHIGEAKI;

    申请日2005-12-08

  • 分类号G06N5/04;G06N3;G06F17/30;G06Q10;G06F19;

  • 国家 JP

  • 入库时间 2022-08-21 21:14:25

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