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The Microsoft Academic Knowledge Graph: A Linked Data Source with 8 Billion Triples of Scholarly Data

Published: 2019

Buchtitel: Proceedings of the 18th International Semantic Web Conference (ISWC'19)
Seiten: 113--129
Verlag: Springer

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In this paper, we present the Microsoft Academic Knowledge Graph (MAKG), a large RDF data set with over eight billion triples with information about scientific publications and related entities, such as authors, institutions, journals, and fields of study. The data set is licensed under the Open Data Commons Attribution License (ODC-By). By providing the data as RDF dump files as well as a data source in the Linked Open Data cloud with resolvable URIs and links to other data sources, we bring a vast amount of scholarly data to the Web of Data. Furthermore, we provide entity embeddings for all 210 million represented publications. We facilitate a number of use case scenarios, particularly in the field of digital libraries, such as (1) entity-centric exploration of papers, researchers, affiliations, etc.; (2) data integration tasks using RDF as a common data model and links to other data sources; and (3) data analysis and knowledge discovery of scholarly data.

Download: Media:MAKG_ISWC2019.pdf
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Verknüpfte Datasets

Microsoft Academic Knowledge Graph


Web Science


Information Retrieval, Wissensrepräsentation, Semantic Web Infrastructure, Digitale Bibliotheken, Semantic Web