A Knowledge Graph for Humanities Research

We create a Knowledge Graph for Humanities research. Starting with a multidisciplinary dataset of 25,000 OCRed JSTOR papers, we use Deep Learning methods to filter out OCR noise, extract and interrelate research activities, methods and goals, associate them with metadata and transform each paper into approximately 200 RDF triples.

Related Organizations

Athens University of Economics and Business
Greece

Keywords

Paper, Long Presentation, Informatics, Knowledge graphs, knowledge representation, information extraction from text, natural language processing, entity recognition, artificial intelligence and machine learning, Computer science, linked (open) data

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average