论文标题
含义的主要组成部分
Principal Components of the Meaning
论文作者
论文摘要
在本文中，我们认为科学中的含义（词汇）可以在13个维度的含义空间中表示。该空间是在单词类别相对信息获得的矩阵上使用主成分分析（单数分解）构建的，其中这些类别是科学网络使用的类别，这些单词是从科学网络中的文本中删除的。我们表明，这种简化的单词集合可以合理地表示语料库中的所有文本，因此主组件分析在语料库中具有一定的客观含义。我们认为，13个维度足以描述科学文本的含义，并假设对主要成分的定性含义。
In this paper we argue that (lexical) meaning in science can be represented in a 13 dimension Meaning Space. This space is constructed using principal component analysis (singular decomposition) on the matrix of word category relative information gains, where the categories are those used by the Web of Science, and the words are taken from a reduced word set from texts in the Web of Science. We show that this reduced word set plausibly represents all texts in the corpus, so that the principal component analysis has some objective meaning with respect to the corpus. We argue that 13 dimensions is adequate to describe the meaning of scientific texts, and hypothesise about the qualitative meaning of the principal components.
