Microsoft Academic Graph: When experts are not enough
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Abstract
An ongoing project explores the extent to which artificial intelligence (AI), specifically in the areas of natural language processing and semantic reasoning, can be exploited to facilitate the studies of science by deploying software agents equipped with natural language understanding capabilities to read scholarly publications on the web. The knowledge extracted by these AI agents is organized into a heterogeneous graph, called Microsoft Academic Graph (MAG), where the nodes and the edges represent the entities engaging in scholarly communications and the relationships among them, respectively. The frequently updated data set and a few software tools central to the underlying AI components are distributed…
Citation impact
500
total citations
- FWCI
- 37.27
- Percentile
- 100%
- References
- 52
Citations per year
Authors
6Topics & keywords
Keywords
- Computer science
- Knowledge graph
- World Wide Web
- Data science
- Semantic Web
- Schema (genetic algorithms)
- License
- Software
UN Sustainable Development Goals
- Quality Education
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