科学与技术是两种不同的制度模式,前者属于科学共和国"Republic of Science",后者属于技术王国"Realm of Technology",两者具有天生的互补性。开放科学作为一种非市场化的激励制度,提出一套基于优先权的报酬体制,...科学与技术是两种不同的制度模式,前者属于科学共和国"Republic of Science",后者属于技术王国"Realm of Technology",两者具有天生的互补性。开放科学作为一种非市场化的激励制度,提出一套基于优先权的报酬体制,强调在知识产权保护前提下追求创新知识社会福利的最大化,对于催生高质量的研究和创新(Research&Innovation)至关重要。本文在阐述开放科学起源、发展与理论内涵的基础上,重点从公共资助、累积创新、知识产权保护和知识分工四个方面,深入探究了开放科学建构的制度逻辑。展开更多
With this work, we introduce a novel method for the unsupervised learning of conceptual hierarchies, or concept maps as they are sometimes called, which is aimed specifically for use with literary texts, as such disti...With this work, we introduce a novel method for the unsupervised learning of conceptual hierarchies, or concept maps as they are sometimes called, which is aimed specifically for use with literary texts, as such distinguishing itself from the majority of research literature on the topic which is primarily focused on building ontologies from a vast array of different types of data sources, both structured and unstructured, to support various forms of AI, in particular, the Semantic Web as envisioned by Tim Berners-Lee. We first elaborate on mutually informing disciplines of philosophy and computer science, or more specifically the relationship between metaphysics, epistemology, ontology, computing and AI, followed by a technically in-depth discussion of DEBRA, our dependency tree based concept hierarchy constructor, which as its name alludes to, constructs a conceptual map in the form of a directed graph which illustrates the concepts, their respective relations, and the implied ontological structure of the concepts as encoded in the text, decoded with standard Python NLP libraries such as spaCy and NLTK. With this work we hope to both augment the Knowledge Representation literature with opportunities for intellectual advancement in AI with more intuitive, less analytical, and well-known forms of knowledge representation from the cognitive science community, as well as open up new areas of research between Computer Science and the Humanities with respect to the application of the latest in NLP tools and techniques upon literature of cultural significance, shedding light on existing methods of computation with respect to documents in semantic space that effectively allows for, at the very least, the comparison and evolution of texts through time, using vector space math.展开更多
文摘科学与技术是两种不同的制度模式,前者属于科学共和国"Republic of Science",后者属于技术王国"Realm of Technology",两者具有天生的互补性。开放科学作为一种非市场化的激励制度,提出一套基于优先权的报酬体制,强调在知识产权保护前提下追求创新知识社会福利的最大化,对于催生高质量的研究和创新(Research&Innovation)至关重要。本文在阐述开放科学起源、发展与理论内涵的基础上,重点从公共资助、累积创新、知识产权保护和知识分工四个方面,深入探究了开放科学建构的制度逻辑。
文摘With this work, we introduce a novel method for the unsupervised learning of conceptual hierarchies, or concept maps as they are sometimes called, which is aimed specifically for use with literary texts, as such distinguishing itself from the majority of research literature on the topic which is primarily focused on building ontologies from a vast array of different types of data sources, both structured and unstructured, to support various forms of AI, in particular, the Semantic Web as envisioned by Tim Berners-Lee. We first elaborate on mutually informing disciplines of philosophy and computer science, or more specifically the relationship between metaphysics, epistemology, ontology, computing and AI, followed by a technically in-depth discussion of DEBRA, our dependency tree based concept hierarchy constructor, which as its name alludes to, constructs a conceptual map in the form of a directed graph which illustrates the concepts, their respective relations, and the implied ontological structure of the concepts as encoded in the text, decoded with standard Python NLP libraries such as spaCy and NLTK. With this work we hope to both augment the Knowledge Representation literature with opportunities for intellectual advancement in AI with more intuitive, less analytical, and well-known forms of knowledge representation from the cognitive science community, as well as open up new areas of research between Computer Science and the Humanities with respect to the application of the latest in NLP tools and techniques upon literature of cultural significance, shedding light on existing methods of computation with respect to documents in semantic space that effectively allows for, at the very least, the comparison and evolution of texts through time, using vector space math.
