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The Computer Science Ontology (CSO) is an automatically generated taxonomy of research topics in the field of Computer Science.cite-ref-1[1]cite-ref-2[2] 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.cite-ref-3[3] Several branches were manually improved by domain experts. The current version (CSO 3.2cite-ref-4[4]) includes about 14K research topics and 160K semantic relationships.cite-ref-salatino19a-5-0[5]

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.cite-ref-6[6]

CSO is mostly used to characterise scientific papers and other documents according to their research areas, in order to enable different kinds of analytics.cite-ref-7[7] The CSO Classifiercite-ref-8[8] is an open-source python tool for automatically annotating documents with CSO.

• Applications

• See also

• References

• External links

• Recommender Systems.cite-ref-9[9]

• Computing the semantic similarity of documents.cite-ref-10[10]

• Extracting metadata from video lecture subtitles.cite-ref-11[11]

• Performing bibliometrics analysis.cite-ref-12[12]

• 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)

cite-note-11. ↑ 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. [1]

cite-note-22. ↑ 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). [2]

cite-note-33. ↑ "Press Release - Springer Nature". 5 January 2020. Retrieved 2020-01-10.

cite-note-44. ↑ "Last version of CSO". 6 July 2020. Retrieved 2020-07-06.

cite-note-salatino19a-55. ↑ 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. [3]

cite-note-66. ↑ "The CSO Portal". Retrieved 4 January 2020.

cite-note-77. ↑ 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. [4]

cite-note-88. ↑ "The CSO Classifier". Retrieved 4 January 2020.

cite-note-99. ↑ 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.[5]

cite-note-1010. ↑ 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. [6]

cite-note-1111. ↑ 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. [7]

cite-note-1212. ↑ 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. [8]

• Official website