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1. 发明授权

US06356864B1 Methods for analysis and evaluation of the semantic content of a writing based on vector length 失效
标题翻译：基于矢量长度的写作语义内容的分析和评估方法
公开(公告)号：US06356864B1
公开(公告)日：2002-03-12
申请号：US09121450
申请日：1998-07-23
申请人： Peter William Foltz , Thomas K. Landauer , Robert Darrell Laham, II , Walter Kintsch , Robert Ernest Rehder
发明人： Peter William Foltz , Thomas K. Landauer , Robert Darrell Laham, II , Walter Kintsch , Robert Ernest Rehder
IPC分类号： G06F1727
CPC分类号： G06F17/2785
摘要： The present invention is a methodology for analyzing and evaluating a sample text, such as essay(s), or document(s). This methodology compares sample text to a reference essay(s), document(s), or text segment(s) within a reference essay or document. The methodology analyzes the amount of subject-matter information in the sample text, analyzes the relevance of subject matter information in the sample and evaluates the semantic coherence of the sample. This methodology presumes there is an underlying, latent semantic structure in the usage of words. The method parses and stores text objects and text segments from the sample text and reference text into a two-dimensional data matrix. A weight is computed for each text object and applied to each data matrix cell value. The method performs a singular value decomposition on the data matrix, which produces three trained matrices. The method computes a vector representation of the sample text and reference text using the three trained matrices. The methodology compares the sample text to the reference text by computing the cosine between the vector representation of the sample text and the vector representation of the standard reference text. Alternatively, the dot product is used to compare the sample text to the standard reference text. A grade is assigned to the sample text based on the degree of similarity between the sample text and the standard reference text.
摘要翻译：本发明是用于分析和评估样本文本（例如散文或文档）的方法。这种方法将样本文本与参考文献或文档中的参考文献，文档或文本段进行比较。该方法分析样本文本中主题信息的数量，分析样本中主题信息的相关性，并评估样本的语义一致性。这种方法假设在使用词语中存在潜在的潜在语义结构。该方法将样本文本和参考文本中的文本对象和文本段解析并存储为二维数据矩阵。为每个文本对象计算权重并应用于每个数据矩阵单元格值。该方法对数据矩阵执行奇异值分解，产生三个训练矩阵。该方法使用三个训练矩阵计算样本文本和参考文本的向量表示。该方法通过计算样本文本的向量表示和标准参考文本的向量表示之间的余弦值将样本文本与参考文本进行比较。或者，点产品用于将样本文本与标准参考文本进行比较。基于样本文本和标准参考文本之间的相似度，将等级分配给样本文本。

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