首页> 外国专利> IDENTITY VECTOR CONSTRUCTION DEVICE, IDENTITY VECTOR CONSTRUCTION METHOD, PREDICATE SIMILARITY CALCULATION DEVICE, PREDICATE SIMILARITY CALCULATION METHOD AND PREDICATE SIMILARITY CALCULATION PROGRAM

IDENTITY VECTOR CONSTRUCTION DEVICE, IDENTITY VECTOR CONSTRUCTION METHOD, PREDICATE SIMILARITY CALCULATION DEVICE, PREDICATE SIMILARITY CALCULATION METHOD AND PREDICATE SIMILARITY CALCULATION PROGRAM

机译:身份向量构造装置,身份向量构造方法,预测相似度计算装置,预测相似度计算方法和预测相似度计算程序

摘要

PROBLEM TO BE SOLVED: To exactly perform synonymous determination between predicates having surface layer character strings different from each other.SOLUTION: A morpheme analysis part performs a morphological analysis of a plurality of sentences. A modification analysis part performs a modification analysis between respective clauses of the plurality of sentences. A semantic label giving part specifies functional expression of a plurality of predicates belonging to the plurality of sentences and gives a semantic label represent the meaning thereof to each functional expression. An identity extraction part extracts a character string representing each functional expression of the plurality of predicates as a first identity on the basis of a morphological analysis result, extracts the semantic label given to each extracted functional expression as a second identity, and extracts a word having a modification relation to each of the plurality of predicates as a third identity. An identity vector construction part constructs an identity vector including the first, second and third identities as elements on the basis of each of the first, second and third identities extracted by identity extraction means about each of the plurality of predicates in each predicate about the plurality of predicates and a mutual information amount with the predicate.
机译:解决的问题:在具有彼此不同的表层字符串的谓词之间准确地进行同义词确定。解决方案:词素分析部分对多个句子进行词法分析。变形分析部在多个句子的各个从句之间进行变形分析。语义标签赋予部分指定属于多个句子的多个谓词的功能表达,并向每个功能表达赋予表示其含义的语义标签。身份提取部分基于形态分析结果提取表示多个谓词的每个功能表达式的字符串作为第一身份,提取赋予每个提取的功能表达式的语义标签作为第二身份,并提取具有与多个谓词中的每个谓词的修改关系作为第三身份。身份向量构造部分基于由身份提取装置提取的关于多个谓词中的每个谓词中的每个谓词的第一,第二和第三身份中的每个身份,构造包括第一,第二和第三身份作为元素的身份向量。谓词的数量以及与谓词的相互信息量。

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