The Computer Science Ontology (CSO) is an automatically generated taxonomy of research topics in the field of Computer Science. Kotis, K.I., Vouros, G.A. and Spiliotopoulos, D., 2020. Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations. The Knowledge Engineering Review, 35. Fathalla, S., Auer, S. and Lange, C., 2020, March. Towards the semantic formalization of science. In Proceedings of the 35th Annual ACM Symposium on Applied Computing (pp. 2057-2059). It was produced by the Open University in collaboration with Springer Nature by running an information extraction system over a large corpus of scientific articles. Several branches were manually improved by domain experts. The current version (CSO 3.2) includes about 14K research topics and 160K semantic relationships.Salatino, A.A., Thanapalasingam, T., Mannocci, A., Birukou, A., Osborne, F. and Motta, E. (2019) The Computer Science Ontology: A Comprehensive Automatically-Generated Taxonomy of Research Areas, Data Intelligence.
CSO is available in OWL, Turtle, and N-Triples. It is aligned with several other knowledge graphs, including DBpedia, Wikidata, YAGO, Freebase, and Cyc. New versions of CSO are regularly released on the CSO Portal.
CSO is mostly used to characterise scientific papers and other documents according to their research areas, in order to enable different kinds of analytics.Zhang, X., Chandrasegaran, S. and Ma, K.L., 2020. ConceptScope: Organizing and Visualizing Knowledge in Documents based on Domain Ontology. arXiv preprint arXiv:2003.05108. The CSO Classifier is an open-source python tool for automatically annotating documents with CSO.
Applications Recommender Systems.Iana, A., Jung, S., Naeser, P., Birukou, A., Hertling, S. and Paulheim, H., 2019, September. Building a conference recommender system based on SciGraph and WikiCFP. In International Conference on Semantic Systems (pp. 117-123). Springer, Cham. Computing the semantic similarity of documents. Supriyati, E., Iqbal, M. and Khotimah, T., 2019. Using similarity degrees to improve fuzzy mining association rule based model for analysing IT entrepreneurial tendency. IIUM Engineering Journal, 20(2), pp.78-89. Extracting metadata from video lecture subtitles.Borges, M.V.M., dos Reis, J.C. and Gribeler, G.P., 2019, June. Empirical Analysis of Semantic Metadata Extraction from Video Lecture Subtitles. In 2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE) (pp. 301-306). IEEE. Performing bibliometrics analysis.Zhang, X., Chandrasegaran, S. and Ma, K.L., 2020. ConceptScope: Organizing and Visualizing Knowledge in Documents based on Domain Ontology. arXiv preprint arXiv:2003.05108.
See also
Ontology (information science) Semantic Web Knowledge graph DBpedia YAGO Freebase Cyc ACM Computing Classification System Mathematics Subject Classification (MSC) Physics and Astronomy Classification Scheme (PACS) PhySH (Physics Subject Headings)
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