Ontology-driven Intelligent IT Incident Management Model
Автор: Bisrat Betru, Fekade Getahun
Журнал: International Journal of Information Technology and Computer Science @ijitcs
Статья в выпуске: 1 Vol. 15, 2023 года.
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A significant number of Information Technology incidents are reported through email. To design and implement an intelligent incident management system, it is significant to automatically classify the reported incident to a given incident category. This requires the extraction of semantic content from the reported email text. In this research work, we have attempted to classify a reported incident to a given category based on its semantic content using ontology. We have developed an Incident Ontology that can serve as a knowledge base for the incident management system. We have also developed an automatic incident classifier that matches the semantical units of the incident report with concepts in the incident ontology. According to our evaluation, ontology-driven incident classification facilitates the process of Information Technology incident management in a better way since the model shows 100% recall, 66% precision, and 79% F1-Score for sample incident reports.
ITIL, Incident Ontology, Ontology-driven Information Extraction, Semantic Text Classification, Intelligent Systems
Короткий адрес: https://sciup.org/15018921
IDR: 15018921 | DOI: 10.5815/ijitcs.2023.01.04
Список литературы Ontology-driven Intelligent IT Incident Management Model
- Galup, S.D., Dattero, R., Quan, J.J., and Conger, S.: ‘An overview of IT service management’, Communications of the ACM, 2009, 52, (5), pp. 124-127.
- Pollard, C., and Cater-Steel, A.: ‘Justifications, strategies, and critical success factors in successful ITIL implementations in US and Australian companies: an exploratory study’, Information systems management, 26, (2), pp. 164-175, 2009. DOI: 10.1080/10580530902797540
- Kneller, M.: ‘Executive briefing: the benefits of ITIL®’, The Stationery Office, UK, 2010.
- Van Bon, J., De Jong, A., Kolthof, A., Pieper, M., Tjassing, R., Van der Veen, A., and Verheijen, T.: ‘Fundamentos de ITIL®’, Van Haren, 2008.
- Brewster, E., Griffiths, R., Lawes, A., and Sansbury, J.: ‘IT service management: a guide for ITIL foundation exam candidates’, BCS, The Chartered Institute for IT, 2012.
- Cusick, J.J., and Ma, G.: ‘Creating an ITIL inspired Incident Management approach: Roots, response, and results’, IEEE, (Ed.): ‘Book Creating an ITIL inspired Incident Management approach: Roots, response, and results’, pp. 142-148, 2010. DOI: 10.1109/NOMSW.2010.5486589
- Berrios, D.C., and Keller, R.M.: ‘Semantic Analysis of Email Using Domain Ontologies and WordNet’, 2005
- Wimalasuriya, D.C., Dou, D., Farley, A., and Young, M.: ‘Ontology-Based Information Extraction’, University of Oregon, 2009.
- Sheth, A.P., and Ramakrishnan, C.: ‘Semantic (Web) technology in action: Ontology driven information systems for search, integration, and analysis’, IEEE Data Engineering Bulletin, vol 26, (4), pp. 40, 2003.
- Staab, S., and Studer, R.: ‘Handbook on ontologies, Springer Science & Business Media, 2010.
- Van Harmelen, F., Lifschitz, V., and Porter, B.: ‘Handbook of knowledge representation’, Elsevier, 2008.
- Miller, S.J.: ‘Introduction to Ontology Concepts and Terminology’, in Editor (Ed.)^(Eds.): ‘Book Introduction to Ontology Concepts and Terminology’ 2013.
- Bench-Capon, T.J.: ‘Knowledge representation: An approach to artificial intelligence’ , Elsevier, 2014.
- Domingue, J., Fensel, D., and Hendler, J.A.: ‘Handbook of semantic web technologies, Springer Science & Business Media, 2011.
- Kaur, N., and Aggarwal, H.: ‘Evaluation of information retrieval based ontology development editors for semantic web’, International Journal of Modern Education and Computer Science, vol 9, (7), pp. 63, 2017.
- Harispe, S., Ranwez, S., Janaqi, S., and Montmain, J.: ‘Semantic similarity from natural language and ontology analysis’, Synthesis Lectures on Human Language Technologies, vol 8, (1), pp. 1-254, 2015. DOI: 10.2200/S00639ED1V01Y201504HLT027
- Karkaletsis, V., Fragkou, P., Petasis, G., and Iosif, E.: ‘Ontology based information extraction from text’: ‘Knowledge-driven multimedia information extraction and ontology evolution’, Springer, pp. 89-109, 2011.
- Embley, D.W.: ‘Toward semantic understanding: an approach based on information extraction ontologies’, in Editor (Ed.)^(Eds.): ‘Book Toward semantic understanding: an approach based on information extraction ontologies’, pp. 3-12, 2004.
- Li, Y., and Bontcheva, K.: ‘Hierarchical, perceptron-like learning for ontology-based information extraction’, in Editor (Ed.)^(Eds.): ‘Book Hierarchical, perceptron-like learning for ontology-based information extraction’, pp. 777-786, 2007.
- Mundie, D.A., Ruefle, R., Dorofee, A.J., Perl, S.J., McCloud, J., and Collins, M.: ‘An Incident Management Ontology’, in Editor (Ed.)^(Eds.): ‘Book An Incident Management Ontology’, pp. 62-71, 2014.
- Freitas, J.M., Correia, A., and e Abreu, F.B.: ‘An Ontology for IT Services’, in Editor (Ed.)^(Eds.): ‘Book An Ontology for IT Services’, pp. 367-372, 2008.
- Czarnecki, A., and Orłowski, C.: ‘Application of Ontology in the ITIL Domain’, 2011.
- Valiente, M.C., Rodríguez, D., and Vicente Chicote, C.: ‘Defining the semantics of IT service management models using OWL and SWRL’, 2010.
- Kleiner, F., Abecker, A., and Mauritczat, M.: ‘Incident and Problem Management using a Semantic Wiki-enabled ITSM Platform’, in Editor (Ed.)^(Eds.): ‘Book Incident and Problem Management using a Semantic Wiki-enabled ITSM Platform’, pp. 363-372, 2012.
- Uschold, M., and King, M.: ‘Towards a methodology for building ontologies’ Citeseer, 1995.
- Mizoguchi, R.: ‘Tutorial on ontological engineering Part 2: Ontology development, tools and languages’, New Generation Computing, vol 22, (1), pp. 61-96, 2004.
- Slimani, T.: ‘Ontology development: A comparing study on tools, languages and formalisms’, Indian Journal of Science and Technology, vol 8, (24), pp. 1-12, 2015. DOI: 10.17485/ijst/2015/v8i34/54249
- Suárez-Figueroa, M.C., de Cea, G.A., and Gómez-Pérez, A.: ‘Lights and shadows in creating a glossary about ontology engineering’, Terminology. International Journal of Theoretical and Applied Issues in Specialized Communication, vol 19, (2), pp. 202-236, 2013. DOI: 10.1075/term.19.2.03sua
- Novalija, I., Mladenić, D., and Bradeško, L.: ‘OntoPlus: Text-driven ontology extension using ontology content, structure and co-occurrence information’, Knowledge-Based Systems, vol 24, (8), pp. 1261-1276, 2011. DOI: 10.1016/j.knosys.2011.06.002
- Meijer, K., Frasincar, F., and Hogenboom, F.: ‘A semantic approach for extracting domain taxonomies from text’, Decision Support Systems, vol 62, pp. 78-93, 2014. DOI: 10.1016/j.dss.2014.03.006
- Witte, R., Khamis, N., and Rilling, J.: ‘Flexible Ontology Population from Text: The OwlExporter’, in Editor (Ed.)^(Eds.): ‘Book Flexible Ontology Population from Text: The OwlExporter’, pp. 3845-3850, 2010.
- Vysniauskas, E., Nemuraite, L., and Paradauskas, B.: ‘Hybrid method for storing and querying ontologies in databases’, Elektronika ir Elektrotechnika, vol 115, (9), pp. 67-72, 2011. DOI: 10.5755/j01.eee.115.9.752
- Zhang, H., Wang, Z., Gao, Z., and Li, W.: ‘Design and implementation of mapping rules from OWL to relational database’, in Editor (Ed.)^(Eds.): ‘Book Design and implementation of mapping rules from OWL to relational database’, IEEE, pp. 71-75, 2009. DOI: 10.1109/CSIE.2009.290
- Smith, R.: ‘Tesseract ocr engine’, Lecture. Google Code. Google Inc, 2007.
- Uysal, A.K., Gunal, S., Ergin, S., and Gunal, E.S.: ‘A novel framework for SMS spam filtering’, in Editor (Ed.)^(Eds.): ‘Book A novel framework for SMS spam filtering’, IEEE, pp. 1-4, 2012. DOI: 10.1109/INISTA.2012.6246947
- Zareapoor, M., and Seeja, K.: ‘Feature extraction or feature selection for text classification: A case study on phishing email detection’, International Journal of Information Engineering and Electronic Business, vol 7, (2), pp. 60, 2015.
- Tan, S., Wang, Y., and Wu, G.: ‘Adapting centroid classifier for document categorization’, Expert Systems with Applications, vol 38, (8), pp. 10264-10273, 2011. DOI: 10.1016/j.eswa.2011.02.114
- OpenNLP, A.: ‘Natural language toolkit’
- Laclavik, M., Šeleng, M., Ciglan, M., and Hluchý, L.: ‘Ontea: Platform for pattern based automated semantic annotation’, Computing and informatics, vol 28, (4), pp. 555–579, 2012.
- Amaral, C.A., Fantinato, M., Reijers, H.A., and Peres, S.M.: ‘Enhancing Completion Time Prediction Through Attribute Selection’: ‘Information Technology for Management: Emerging Research and Applications’, Springer, pp. 3-23, 2018. DOI: 10.1007/978-3-030-15154-6_1
- Lord, P.W., Stevens, R.D., Brass, A., and Goble, C.A.: ‘Investigating semantic similarity measures across the Gene Ontology: the relationship between sequence and annotation’, Bioinformatics, vol 19, (10), pp. 1275-1283, 2003. DOI: 10.1093/bioinformatics/btg153
- ItSMF, U.: ‘ITIL Foundation Handbook’, The Stationery Office, 2012.
- Ray, S., and Chandra, N., "Domain based ontology and automated text categorization based on improved term frequency-Inverse document frequency", International Journal of Modern Education and Computer Science, vol 4, No.1, pp. 28-35, 2012.
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