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Salatino, Angelo; Osborne, Francesco and Motta, Enrico
(2020).
DOI: https://doi.org/10.3233/SSW200037
Abstract
Ontologies of research areas have been proven to be useful resources for analysing and making sense of scholarly data. In this chapter, we present the Computer Science Ontology (CSO), which is the largest ontology of research areas in the field, and discuss a number of applications that build on CSO to support high-level tasks, such as topic classification, metadata extraction, and recommendation of books.
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About
- Item ORO ID
- 72232
- Item Type
- Book Section
- Keywords
- Scholarly Data;Ontology Learning;Bibliographic Data;Scholarly Ontologies
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Research Group
- eSTEeM
- Depositing User
- Francesco Osborne