Ontologies of research areas have been proven to be useful in many application for analysing and making sense of scholarly data. In this lecture, I will present how we produced the Computer Science Ontology (CSO), which is the largest ontology of research areas in the field of Computer Science, and discuss a number of applications that build on CSO, to support high-level tasks, such as topic classification, research trends forecasting, metadata extraction, and recommendation of books.
Recent Posts
- AI for the Research Ecosystem workshop #AI4RE – round up 30 March 2024
- Integrating Conversational Agents and Knowledge Graphs Within the Scholarly Domain 18 March 2023
- R-Classify: Extracting Research Papers’ Relevant Concepts from a Controlled Vocabulary 12 November 2022
- Leveraging Knowledge Graph Technologies to Assess Journals and Conferences at Springer Nature 12 November 2022
- Best Paper Award at the In-Use Track ISWC 2022 12 November 2022
- Annotating D3 dataset with the CSO Classifier 20 September 2022
- Sci-K 2022 – International Workshop on Scientific Knowledge: Representation, Discovery, and Assessment 17 June 2022
- Enriching Data Lakes with Knowledge Graphs 17 June 2022
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