Karyon: A scalable and easy to integrate ontology summarisation framework

Ozacar T., ÖZTÜRK Ö.

Journal of Information Science, cilt.47, sa.2, ss.255-268, 2021 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 47 Sayı: 2
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1177/0165551519887873
  • Dergi Adı: Journal of Information Science
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, FRANCIS, IBZ Online, Periodicals Index Online, ABI/INFORM, Aerospace Database, Analytical Abstracts, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, EBSCO Education Source, Education Abstracts, Index Islamicus, Information Science and Technology Abstracts, INSPEC, Library and Information Science Abstracts, Library Literature and Information Science, Library, Information Science & Technology Abstracts (LISTA), Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.255-268
  • Anahtar Kelimeler: Key concepts, ontology, ontology summarisation, Rust
  • Manisa Celal Bayar Üniversitesi Adresli: Evet

Özet

In the current Semantic Web Community, as the size and complexity of ontologies increase, ontology summarisation is becoming more important. There are many studies in the literature that use different approaches and metrics. However, many of these studies are not effective in terms of performance or have integration issues with current technologies. In this study, the popular ontology summarisation metrics are examined focusing on their performance in terms of time, and a number of metrics have been selected accordingly. To increase the accuracy of selections made with chosen metrics, we propose a novel metric: ‘name inclusion’. This metric promotes a concept if its name is subsumed by the name of another concept. As the existing summarisation applications have integration issues, we have implemented our summarisation framework to integrate easily with the latest web technologies. Therefore, the algorithm is implemented using Rust language, which performs well and easily integrates with other languages.