Machine Learning the Daoist Canon through Text Mining Semantic Analysis and Philosophical Pattern Recognition

Abstract

Abstract: This Study of the intersection of machine learning and Daoist philosophy can lead to a new level of understanding of the contents of the Daoist Canon. Natural Language Processing (NLP) studies the ways in which humans interact with computers by means of language. As such, it provides powerful tools for study of very large corpora of text, such as the writings of the Daoist sages. Here, machine learning algorithms can be applied in order to automatically discover the key philosophical concepts, their linguistic realization, and intertextual connections, and the Digital Humanities application of such study of the Daoist classics can be used to enrich traditional studies and provide easy access to them for a wider audience of scholars and the interested public alike. The studies employing computer-assisted methodologies to analyze the ancient philosophical heritage also make possible a new perspective on the legacy, fostering a dialogue between the ancient wisdom and modern technology. This research also has implications for the development of academic studies of Daoism and for the wider study of machine learning in the Humanities, in general, highlighting the possibilities and limitations of computer-assisted knowledge production.