书面语语义信息的量化研究
Towards the quantification of the semantic information encoded in written language
摘要：
书面语言是一种复杂的通信信号，能够以有序的单词序列的形式传达信息。除了语法所规定的局部顺序之外，语义和主题结构也影响着词汇使用的长期模式。在这里，我们表明，直接应用信息理论量化的统计分布的单词和文本的语义内容之间的关系。我们发现，有一个特征的规模，大约几千字，建立了典型的大小最翔实的部分在书面语言。此外，我们还发现，那些对整体信息贡献较大的词，往往与文章的主题和主题联系得更紧密。这种情况可以用一个词语使用模型来解释，该模型假设词语沿着文本分布在具有特征大小的域中，这些域的频率高于其他地方。我们的结论是基于一个大型数据库的书面语言，不同的主题和风格的分析，因此可能适用于一般的语言序列编码复杂的信息。
英文摘要：
Written language is a complex communication signal capable of conveying information encoded in the form of ordered sequences of words. Beyond the local order ruled by grammar, semantic and thematic structures affect long-range patterns in word usage. Here, we show that a direct application of information theory quantifies the relationship between the statistical distribution of words and the semantic content of the text. We show that there is a characteristic scale, roughly around a few thousand words, which establishes the typical size of the most informative segments in written language. Moreover, we find that the words whose contributions to the overall information is larger, are the ones more closely associated with the main subjects and topics of the text. This scenario can be explained by a model of word usage that assumes that words are distributed along the text in domains of a characteristic size where their frequency is higher than elsewhere. Our conclusions are based on the analysis of a large database of written language, diverse in subjects and styles, and thus are likely to be applicable to general language sequences encoding complex information.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
