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ADOL: a novel framework for automatic domain ontology learning

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Abstract

Ontology, as a semantic representation of a shared conceptualization, makes knowledge machine-readable and easy to spread. One of its typical applications is used to develop e-learning systems with Educational Ontology. Ontology can help students master knowledge architecture of required subjects and make scattered courseware more systematic. A big challenge is how to construct Educational Ontology to describe systematic knowledge of different subjects automatically. Currently, most of the ontologies are developed and extended manually, which requires the developers to possess certain professional knowledge and is time-consuming. In this paper, a framework to construct and extend Educational Ontology automatically is proposed.2 The proposed ontology learning framework, called ‘ADOL,’ can convert domain textbooks into a corresponding ontology automatically and efficiently. A case study on High School Physics shows that our approach is feasible and efficient.

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Notes

  1. https://en.wikipedia.org/wiki/Freebase.

  2. https://wiki.dbpedia.org/.

  3. https://wordnet.princeton.edu/.

  4. https://www.w3.org/TR/rdf-schema/.

  5. CN-DBpedia is a large-scale domain structured encyclopedia developed and maintained by the Knowledge Workshop Laboratory of Fudan University.

  6. Zhishi.me is a Chinese Linking Open Data Base. Currently, it covers three largest Chinese encyclopedias: Baidu Baike, Hudong Baike and Chinese Wikipedia. It is developed by Gowild Technology Company and Southeast University.

  7. https://www.w3.org/TR/owl2-overview/.

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Authors and Affiliations

  1. East China Normal University, 3663 North Zhongshan Road, Putuo District, Shanghai, China

    Jizhi Chen & Junzhong Gu

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  1. Jizhi Chen
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  2. Junzhong Gu
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Correspondence to Jizhi Chen.

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Chen, J., Gu, J. ADOL: a novel framework for automatic domain ontology learning. J Supercomput 77, 152–169 (2021). https://doi.org/10.1007/s11227-020-03261-7

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