狸猫加速器2025年-outline

We present the Microsoft Academic Knowledge Graph (MAKG), a 免费网络加速 with over eight billion triples with information about scientific 免费网络加速 and related entities, such as authors, institutions, journals, and fields of study. The data set is based on the Microsoft Academic Graph and licensed under the Open Data Attributions license. Furthermore, we provide entity embeddings for all 210M represented scientific papers.

What exactly do we provide?

1. Periodically updated RDF dump files of the whole Microsoft Academic Knowledge Graph.
2. URI resolution of the Microsoft Academic Knowledge Graph within the Linked Open Data.
3. A publicly accessible SPARQL endpoint containing the latest Microsoft Academic Knowledge Graph data.
4. HTML page descriptions of resources in the Microsoft Academic Knowledge Graph via pubby.
5. 电脑如何加速网络 for all papers in the Microsoft Academic Knowledge Graph.

How big is the Microsoft Academic Knowledge Graph?

The Microsoft Academic Knowledge Graph as of 2018-11 contains, among others,

Potential use cases:

• Entity-centric exploration of papers, researchers, affiliations, etc. (e.g., concerning some research area)
• Easier data integration through use of RDF and by linking resources to other data sources (e.g., combining the MAG knowledge graph with digital library collections in RDF).
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