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CLASSIFICATION MODEL LEARNING METHOD, DEVICE, PROGRAM, AND REVIEW DOCUMENT CLASSIFYING METHOD

机译:分类模型学习方法,设备,程序和审查文档分类方法

摘要

PROBLEM TO BE SOLVED: To properly classify whether documents are review documents or not, from the small amount of learning data.SOLUTION: A sentence dividing portion 22 divides each of a plurality of blog documents for learning which include review documents, in which information about a specified object is written, in a sentence unit. A morphological analyzing portion 23 performs morphological analysis processing to each sentence, and an identity extracting portion 24 extracts identities indicating characteristics of the sentence about each sentence of the blog documents for learning. A learning portion 25 uses each of the extracted identities about each sentence of the blog documents for learning which are the review documents as learning data of positive examples, and each of the extracted identities about each sentence of the blog documents for learning which are not the review documents as learning data of negative examples, thereby learning a classification model for classifying whether the inputted sentences are sentences in the review documents or not.
机译:解决的问题:从少量的学习数据中适当地分类文档是否为评论文档。解决方案:句子划分部分22将包括评论文档的学习用博客文档中的每一个划分为多个,其中关于评论的信息以句子为单位写入指定的对象。形态分析部分23对每个句子执行形态分析处理,并且身份提取部分24提取关于用于学习的博客文档的每个句子的指示句子特征的身份。学习部分25使用关于作为评论示例的学习文档的用于学习的博客文档的每个句子的提取的身份中的每一个,以及关于不是学习者博客文档的用于学习的句子的每个句子的提取的身份中的每个实例。通过将评论文档作为否定示例的学习数据,从而学习用于对输入的句子是否是评论文档中的句子进行分类的分类模型。

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