A machine learning domain ontology to populate knowledge base to support intelligent agents working in autonomous systems domains of the Internet infrastructure
Resumo
Este artigo descreve a criação de uma ontologia de domínio para representar conhecimento para popular uma base de conhecimento a ser usada por agentes, no ambiente dos domínios de roteamento da Infraestrutura da Internet. Foi utilizado o Protégé 5, que produz resultados adequados tanto para agentes desenvolvidos por software como para seres humanos. O conhecimento criado pelo Protégé é explícito e o próprio Protégé tem máquinas de inferência capazes de produzir conhecimento implícito. Os recursos disponíveis no Protégé 5 são exibidos e a ontologia é disponibilizada para uso público, em todas as suas versões. O conteúdo produzido pelo Protégé 5 será utilizado para povoar a base de conhecimento da Estrutura de Aquisição, Uso, Aprendizagem e Colaboração de Conhecimento (SKAU), um ambiente para apoiar agentes inteligentes nos domínios de Sistemas Autônomos da Internet.
Palavras-chave:
infraestrutura da internet, sistemas autonomos, base de conhecimento, agentes inteligentes, ontologia
Referências
ANTONIOU, G.; HARMELEN, F. V. Web ontology language: Owl. In: Handbook on ontologies. [S.l.]: Springer, 2004. p. 67–92.
ARBIX, G. A trAnspArênciA no centro dA construção de umA iA éticA. Novos estudos CEBRAP, SciELO Brasil, v. 39, n. 2, p. 395–413, 2020.
ARDJANI, F.; BOUCHIHA, D.; MALKI, M. Ontology-alignment techniques: Survey and analysis. International Journal of Modern Education & Computer Science, v. 7, n. 11, 2015.
ASIM, M. N.; WASIM, M.; KHAN, M. U. G.; MAHMOOD, W.; ABBASI, H. M. A survey of ontology learning techniques and applications. Database, Narnia, v. 2018, 2018.
BELLE, V.; PAPANTONIS, I. Principles and practice of explainable machine learning. arXiv preprint arXiv:2009.11698, 2020.
BHAVSAR, K.; KUMAR, N.; DANGETI, P. Natural language processing with python cookbook: Over 60 recipes to implement text analytics solutions using deep learning principles. Packt Publishing, 2017.
BIRD, S.; KLEIN, E.; LOPER, E. Natural language processing with Python. [S.l.]: " O’Reilly Media, Inc.", 2009.
BORST, W. N. Construction of engineering ontologies for knowledge sharing and reuse. Tese (Doutorado) — University of Twente, 1997.
BRAGA, J. Ambiente para Aquisição de Conhecimento por Agentes em Domínios Restritos na Infraestrutura da Internet. Tese (Doutorado)—Instituto Superior Técnico & Universidade Presbiteriana Mackenzie, 2019. DOI: 10.31237/osf.io/nzmtf, Availaible in https://thesiscommons.org/nzmtf/.
BRAGA, J. Environment for Knowledge Acquisition by Agents in Internet InfrastructureRestricted Domains. Tese (Doutorado)—Instituto Superior Tecnico & Universidade Presbiteriana Mackenzie, 2019. DOI: 10.31237/osf.io/83ztf. English version translated by author. Available in https://thesiscommons.org/83ztf/.
BRAGA, J.; DIAS, J. L. R.; REGATEIRO, F. A machine learing ontology. Frenxiv, Oct 2020. Preprint. DOI: 10.31226/osf.io/rc954. Available at https://frenxiv.org/rc954/.
BRAGA, J.; NOBRE, J. C.; GRANVILLE, L. Z.; SANTOS, M. Como Protocolos Inovadores são Criados e Adotados em Escala Mundial: Uma visão sobre o Internet Engineering Task Force (IETF) e a Infraestrutura da Internet. In: WEBER, T. S.; MARTINS, C. A. (Ed.). Jornadas de Atualização em Informática 2020. Cuiabá, MT Brazil: Sociedade Brasileira de Computação, 2020. p. 45. ISBN 978-65-87003-28-3. Available in: https://doi.org/10.5753/sbc.5728.3.2.
BRAGA, J.; REGATEIRO, F.; DIAS, J. Machine Learning Ontology (MLOnto) Repository. 2020. Project Repository: OSF. DOI: 10.17605/OSF.IO/CHU5Q. Available in:.
BRAGA, J.; SILVA, J. N.; ENDO, P.; OMAR, N. Structure for knowledge acquisition, use, learning and collaboration inter agents over internet infrastructure domains: Proceedings of the 2019 computing conference. In: ARAI, K.; BHATIA, R.; KAPOOR, S. (Ed.). Intelligent Computing. [S.l.]: Springer International Publishing, 2019. v. 1, p. 527–547. Doi: 10.1007/978-3-030-22871-2, ISBN: 978-3-030-22871-2.
BRANK, J.; GROBELNIK, M.; MLADENIC, D. A survey of ontology evaluation techniques. In: Proceedings of the conference on data mining and data warehouses (SiKDD 2005). Ljubljana, Slovenia: SiKDD, 2005. p. 166–170.
BUITELAAR, P.; CIMIANO, P.; MAGNINI, B. Ontology learning from text: An overview. Ontology learning from text: Methods, evaluation and applications, IOS Press, Amsterdam, v. 123, p. 3–12, 2005.
BUITELAAR, P.; OLEJNIK, D.; SINTEK, M. A protégé plug-in for ontology extraction from text based on linguistic analysis. In: SPRINGER. European Semantic Web Symposium. [S.l.], 2004. p. 31–44.
CARLSON, A.; BETTERIDGE, J.; KISIEL, B.; SETTLES, B.; HRUSCHKA, E. R.; MITCHELL, T. M. Toward an architecture for never-ending language learning. In: Twenty-Fourth AAAI Conference on Artificial Intelligence. Atlanta, US: AAAI Publications, 2010. p. 8.
CIMIANO, P.; VÖLKER, J. A framework for ontology learning and data-driven change discovery. In: SPRINGER. Proceedings of the 10th International Conference on Applications of Natural Language to Information Systems (NLDB). [S.l.], 2005. p. 227–238.
DOAN, A.; MADHAVAN, J.; DOMINGOS, P.; HALEVY, A. Ontology matching: A machine learning approach. In: Handbook on ontologies. [S.l.]: Springer, 2004. p. 385–403.
EHRIG, M. Ontology Alignment: Bridging the Semantic Gap. 1. ed. Germany: Springer, 2007.
FU, H.; CHI, Z.; FENG, D.; SONG, J. Machine learning techniques for ontology-based leaf classification. In: IEEE. ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004. [S.l.], 2004. v. 1, p. 681–686.
GOLBREICH, C.; DAMERON, O.; GIBAUD, B.; BURGUN, A. Web ontology language requirements wrt expressiveness of taxonomy and axioms in medicine. In: SPRINGER. International Semantic Web Conference. [S.l.], 2003. p. 180–194.
GRUBER, T. R. A translation approach to portable ontology specifications. Knowledge Acquisition, v. 5, p. 199–220, 1993.
GUARINO, N.; OBERLE, D.; STAAB, S. What is an ontology? In: Handbook on ontologies. [S.l.]: Springer, 2009. p. 1–17.
GUIZZARDI, G.; WAGNER, G.; ALMEIDA, J. P. A.; GUIZZARDI, R. S. Towards ontological foundations for conceptual modeling: The unified foundational ontology (ufo) story. Applied ontology, IOS Press, v. 10, n. 3-4, p. 259–271, 2015.
HITZLER, P.; KRöTZSCH, M.; PARSIA, B.; PATEL-SCHNEIDER, P. F.; RUDOLPH, S. OWL 2 Web Ontology Language Primer. W3C Recommendation, v. 27, n. 1, p. 1–123, 2009. Available in: https://www.w3.org/TR/owl2-primer/
HORRIDGE, M. A Practical Guide To Building OWL Ontologies Using Protégé 4 and CO-ODE Tools Edition 1.3. [S.l.], 2011. 108 p. Disponível em: https://www.researchgate.net/publication/230585369_A_Practical_Guide_To_Building_OWL_Ontologies_Using_The_Prot%27eg%27e-OWL_Plugin_and_CO-ODE_Tools.
ICHISE, R. Machine learning approach for ontology mapping using multiple concept similarity measures. In: IEEE. Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008). [S.l.], 2008. p. 340–346.
KALIBATIENE, D.; VASILECAS, O. Survey on ontology languages. In: SPRINGER. International Conference on Business Informatics Research. [S.l.], 2011. p. 124–141.
KONYS, A. Knowledge systematization for ontology learning methods. Procedia computer science, Elsevier, v. 126, p. 2194–2207, 2018.
MITCHELL, T.; COHEN, W.; HRUSCHKA, E.; TALUKDAR, P.; YANG, B.; BETTERIDGE, J.; CARLSON, A.; DALVI, B.; GARDNER, M.; KISIEL, B. et al. Never-ending learning. Communications of the ACM, v. 61, n. 5, p. 103–115, 2018.
MUSEN, M. A. The protégé project: a look back and a look forward. AI Matters, v. 1, n. 4, p. 4–12, 2015. Disponível em: https://doi.org/10.1145/2757001.2757003.
PEASE, A. Ontology. [S.l.]: Articulate Software Press, 2011. ISBN: 1889455105. POON, H.; DOMINGOS, P. Unsupervised ontology induction from text. In: Proceedings of the 48th annual meeting of the Association for Computational Linguistics. [S.l.: s.n.], 2010. p. 296–305.
REN, F. A demo for constructing domain ontology from academic papers. In: Proceedings of COLING 2012: Demonstration Papers. [S.l.: s.n.], 2012. p. 369–376.
SACHA, D.; KRAUS, M.; KEIM, D. A.; CHEN, M. Vis4ml: An ontology for visual analytics assisted machine learning. IEEE transactions on visualization and computer graphics, IEEE, v. 25, n. 1, p. 385–395, 2018.
SHAMSFARD, M.; BARFOROUSH, A. A. Learning ontologies from natural language texts. International journal of human-computer studies, Elsevier, v. 60, n. 1, p. 17–63, 2004.
SHEKHAR, M.; K, S. R. Semantic Web Search based on Ontology Modeling using Protege Reasoner. 2013.
SILVER, D. L.; YANG, Q.; LI, L. Lifelong machine learning systems: Beyond learning algorithms. In: 2013 AAAI spring symposium series. [S.l.: s.n.], 2013.
SLIMANI, T. Ontology development: A comparing study on tools, languages and formalisms. Indian Journal of Science and Technology, v. 8, n. 24, p. 1–12, 2015.
STUDER, R.; BENJAMINS, V. R.; FENSEL, D. Knowledge engineering: principles and methods. Data & knowledge engineering, Elsevier, v. 25, n. 1-2, p. 161–197, 1998.
TAN, H.; LAMBRIX, P. Selecting an ontology for biomedical text mining. In: Proceedings of the BioNLP 2009 Workshop. [S.l.: s.n.], 2009. p. 55–62.
TUDORACHE, T.; NYULAS, C.; NOY, N. F.; MUSEN, M. A. Webprotégé: A collaborative ontology editor and knowledge acquisition tool for the web. Semantic web, IOS Press, v. 4, n. 1, p. 89–99, 2013.
XIAO, G.; DING, L.; COGREL, B.; CALVANESE, D. Virtual knowledge graphs: An overview of systems and use cases. Data Intelligence, MIT Press, v. 1, n. 3, p. 201–223, 2019.
XIAO, G.; LANTI, D.; KONTCHAKOV, R.; KOMLA-EBRI, S.; GÜZEL-KALAYCI, E.; DING, L.; CORMAN, J.; COGREL, B.; CALVANESE, D.; BOTOEVA, E. The virtual knowledge graph system ontop. In: SPRINGER. International Semantic Web Conference. [S.l.], 2020. p. 259–277.
ARBIX, G. A trAnspArênciA no centro dA construção de umA iA éticA. Novos estudos CEBRAP, SciELO Brasil, v. 39, n. 2, p. 395–413, 2020.
ARDJANI, F.; BOUCHIHA, D.; MALKI, M. Ontology-alignment techniques: Survey and analysis. International Journal of Modern Education & Computer Science, v. 7, n. 11, 2015.
ASIM, M. N.; WASIM, M.; KHAN, M. U. G.; MAHMOOD, W.; ABBASI, H. M. A survey of ontology learning techniques and applications. Database, Narnia, v. 2018, 2018.
BELLE, V.; PAPANTONIS, I. Principles and practice of explainable machine learning. arXiv preprint arXiv:2009.11698, 2020.
BHAVSAR, K.; KUMAR, N.; DANGETI, P. Natural language processing with python cookbook: Over 60 recipes to implement text analytics solutions using deep learning principles. Packt Publishing, 2017.
BIRD, S.; KLEIN, E.; LOPER, E. Natural language processing with Python. [S.l.]: " O’Reilly Media, Inc.", 2009.
BORST, W. N. Construction of engineering ontologies for knowledge sharing and reuse. Tese (Doutorado) — University of Twente, 1997.
BRAGA, J. Ambiente para Aquisição de Conhecimento por Agentes em Domínios Restritos na Infraestrutura da Internet. Tese (Doutorado)—Instituto Superior Técnico & Universidade Presbiteriana Mackenzie, 2019. DOI: 10.31237/osf.io/nzmtf, Availaible in https://thesiscommons.org/nzmtf/.
BRAGA, J. Environment for Knowledge Acquisition by Agents in Internet InfrastructureRestricted Domains. Tese (Doutorado)—Instituto Superior Tecnico & Universidade Presbiteriana Mackenzie, 2019. DOI: 10.31237/osf.io/83ztf. English version translated by author. Available in https://thesiscommons.org/83ztf/.
BRAGA, J.; DIAS, J. L. R.; REGATEIRO, F. A machine learing ontology. Frenxiv, Oct 2020. Preprint. DOI: 10.31226/osf.io/rc954. Available at https://frenxiv.org/rc954/.
BRAGA, J.; NOBRE, J. C.; GRANVILLE, L. Z.; SANTOS, M. Como Protocolos Inovadores são Criados e Adotados em Escala Mundial: Uma visão sobre o Internet Engineering Task Force (IETF) e a Infraestrutura da Internet. In: WEBER, T. S.; MARTINS, C. A. (Ed.). Jornadas de Atualização em Informática 2020. Cuiabá, MT Brazil: Sociedade Brasileira de Computação, 2020. p. 45. ISBN 978-65-87003-28-3. Available in: https://doi.org/10.5753/sbc.5728.3.2.
BRAGA, J.; REGATEIRO, F.; DIAS, J. Machine Learning Ontology (MLOnto) Repository. 2020. Project Repository: OSF. DOI: 10.17605/OSF.IO/CHU5Q. Available in:
BRAGA, J.; SILVA, J. N.; ENDO, P.; OMAR, N. Structure for knowledge acquisition, use, learning and collaboration inter agents over internet infrastructure domains: Proceedings of the 2019 computing conference. In: ARAI, K.; BHATIA, R.; KAPOOR, S. (Ed.). Intelligent Computing. [S.l.]: Springer International Publishing, 2019. v. 1, p. 527–547. Doi: 10.1007/978-3-030-22871-2, ISBN: 978-3-030-22871-2.
BRANK, J.; GROBELNIK, M.; MLADENIC, D. A survey of ontology evaluation techniques. In: Proceedings of the conference on data mining and data warehouses (SiKDD 2005). Ljubljana, Slovenia: SiKDD, 2005. p. 166–170.
BUITELAAR, P.; CIMIANO, P.; MAGNINI, B. Ontology learning from text: An overview. Ontology learning from text: Methods, evaluation and applications, IOS Press, Amsterdam, v. 123, p. 3–12, 2005.
BUITELAAR, P.; OLEJNIK, D.; SINTEK, M. A protégé plug-in for ontology extraction from text based on linguistic analysis. In: SPRINGER. European Semantic Web Symposium. [S.l.], 2004. p. 31–44.
CARLSON, A.; BETTERIDGE, J.; KISIEL, B.; SETTLES, B.; HRUSCHKA, E. R.; MITCHELL, T. M. Toward an architecture for never-ending language learning. In: Twenty-Fourth AAAI Conference on Artificial Intelligence. Atlanta, US: AAAI Publications, 2010. p. 8.
CIMIANO, P.; VÖLKER, J. A framework for ontology learning and data-driven change discovery. In: SPRINGER. Proceedings of the 10th International Conference on Applications of Natural Language to Information Systems (NLDB). [S.l.], 2005. p. 227–238.
DOAN, A.; MADHAVAN, J.; DOMINGOS, P.; HALEVY, A. Ontology matching: A machine learning approach. In: Handbook on ontologies. [S.l.]: Springer, 2004. p. 385–403.
EHRIG, M. Ontology Alignment: Bridging the Semantic Gap. 1. ed. Germany: Springer, 2007.
FU, H.; CHI, Z.; FENG, D.; SONG, J. Machine learning techniques for ontology-based leaf classification. In: IEEE. ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004. [S.l.], 2004. v. 1, p. 681–686.
GOLBREICH, C.; DAMERON, O.; GIBAUD, B.; BURGUN, A. Web ontology language requirements wrt expressiveness of taxonomy and axioms in medicine. In: SPRINGER. International Semantic Web Conference. [S.l.], 2003. p. 180–194.
GRUBER, T. R. A translation approach to portable ontology specifications. Knowledge Acquisition, v. 5, p. 199–220, 1993.
GUARINO, N.; OBERLE, D.; STAAB, S. What is an ontology? In: Handbook on ontologies. [S.l.]: Springer, 2009. p. 1–17.
GUIZZARDI, G.; WAGNER, G.; ALMEIDA, J. P. A.; GUIZZARDI, R. S. Towards ontological foundations for conceptual modeling: The unified foundational ontology (ufo) story. Applied ontology, IOS Press, v. 10, n. 3-4, p. 259–271, 2015.
HITZLER, P.; KRöTZSCH, M.; PARSIA, B.; PATEL-SCHNEIDER, P. F.; RUDOLPH, S. OWL 2 Web Ontology Language Primer. W3C Recommendation, v. 27, n. 1, p. 1–123, 2009. Available in: https://www.w3.org/TR/owl2-primer/
HORRIDGE, M. A Practical Guide To Building OWL Ontologies Using Protégé 4 and CO-ODE Tools Edition 1.3. [S.l.], 2011. 108 p. Disponível em: https://www.researchgate.net/publication/230585369_A_Practical_Guide_To_Building_OWL_Ontologies_Using_The_Prot%27eg%27e-OWL_Plugin_and_CO-ODE_Tools.
ICHISE, R. Machine learning approach for ontology mapping using multiple concept similarity measures. In: IEEE. Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008). [S.l.], 2008. p. 340–346.
KALIBATIENE, D.; VASILECAS, O. Survey on ontology languages. In: SPRINGER. International Conference on Business Informatics Research. [S.l.], 2011. p. 124–141.
KONYS, A. Knowledge systematization for ontology learning methods. Procedia computer science, Elsevier, v. 126, p. 2194–2207, 2018.
MITCHELL, T.; COHEN, W.; HRUSCHKA, E.; TALUKDAR, P.; YANG, B.; BETTERIDGE, J.; CARLSON, A.; DALVI, B.; GARDNER, M.; KISIEL, B. et al. Never-ending learning. Communications of the ACM, v. 61, n. 5, p. 103–115, 2018.
MUSEN, M. A. The protégé project: a look back and a look forward. AI Matters, v. 1, n. 4, p. 4–12, 2015. Disponível em: https://doi.org/10.1145/2757001.2757003.
PEASE, A. Ontology. [S.l.]: Articulate Software Press, 2011. ISBN: 1889455105. POON, H.; DOMINGOS, P. Unsupervised ontology induction from text. In: Proceedings of the 48th annual meeting of the Association for Computational Linguistics. [S.l.: s.n.], 2010. p. 296–305.
REN, F. A demo for constructing domain ontology from academic papers. In: Proceedings of COLING 2012: Demonstration Papers. [S.l.: s.n.], 2012. p. 369–376.
SACHA, D.; KRAUS, M.; KEIM, D. A.; CHEN, M. Vis4ml: An ontology for visual analytics assisted machine learning. IEEE transactions on visualization and computer graphics, IEEE, v. 25, n. 1, p. 385–395, 2018.
SHAMSFARD, M.; BARFOROUSH, A. A. Learning ontologies from natural language texts. International journal of human-computer studies, Elsevier, v. 60, n. 1, p. 17–63, 2004.
SHEKHAR, M.; K, S. R. Semantic Web Search based on Ontology Modeling using Protege Reasoner. 2013.
SILVER, D. L.; YANG, Q.; LI, L. Lifelong machine learning systems: Beyond learning algorithms. In: 2013 AAAI spring symposium series. [S.l.: s.n.], 2013.
SLIMANI, T. Ontology development: A comparing study on tools, languages and formalisms. Indian Journal of Science and Technology, v. 8, n. 24, p. 1–12, 2015.
STUDER, R.; BENJAMINS, V. R.; FENSEL, D. Knowledge engineering: principles and methods. Data & knowledge engineering, Elsevier, v. 25, n. 1-2, p. 161–197, 1998.
TAN, H.; LAMBRIX, P. Selecting an ontology for biomedical text mining. In: Proceedings of the BioNLP 2009 Workshop. [S.l.: s.n.], 2009. p. 55–62.
TUDORACHE, T.; NYULAS, C.; NOY, N. F.; MUSEN, M. A. Webprotégé: A collaborative ontology editor and knowledge acquisition tool for the web. Semantic web, IOS Press, v. 4, n. 1, p. 89–99, 2013.
XIAO, G.; DING, L.; COGREL, B.; CALVANESE, D. Virtual knowledge graphs: An overview of systems and use cases. Data Intelligence, MIT Press, v. 1, n. 3, p. 201–223, 2019.
XIAO, G.; LANTI, D.; KONTCHAKOV, R.; KOMLA-EBRI, S.; GÜZEL-KALAYCI, E.; DING, L.; CORMAN, J.; COGREL, B.; CALVANESE, D.; BOTOEVA, E. The virtual knowledge graph system ontop. In: SPRINGER. International Semantic Web Conference. [S.l.], 2020. p. 259–277.
Publicado
18/07/2021
Como Citar
BRAGA, Julião; REGATEIRO, Francisco; DIAS, Joaquim L. R.; STIUBIENER, Itana.
A machine learning domain ontology to populate knowledge base to support intelligent agents working in autonomous systems domains of the Internet infrastructure. In: WORKSHOP PRÉ-IETF (WPIETF), 8. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 1-12.
ISSN 2595-6388.
DOI: https://doi.org/10.5753/wpietf.2021.15778.
