Abstract
The practice of using ontology to understand a field of study through the analysis of keywords was not found to have been documented, and a five-step method is therefore presented to generate ontologies of keywords: data selection and extraction, data unification strategy, keyword processing, weight and connection standardisation and final representation. Using the proposed method, an experimental evaluation was undertaken using as the field of study the digital transformation in universities and university institutions, generating a knowledge graph that enables the clear visualisation of the various connections among different topics in a chosen field of study. Finally, the effectiveness and the observed limitations are discussed while stressing that each researcher should perform a thorough analysis of those relationships, enabling to obtain useful information for teaching and learning processes, especially in higher education environments.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Borgman, C.L., Hirsh, S.G., Hiller, J.: Rethinking online monitoring methods for information retrieval systems: from search product to search process. J. Am. Soc. Inf. Sci. 47(7), 568–583 (1996)
Abbasi, A.A., Kulathuramaiyer, N.: A systematic mapping study of database resources to ontology via reverse engineering. Asian J. Inf. Technol. 15(4), 730–737 (2016)
Tedesco, J.C.: Educación y sociedad del conocimiento y de la información. Revista Colombiana De Educación, 36–37 (1998)
Medina-López, C., Marín-García, J.A., Alfalla-Luque, R.: Una propuesta metodológica para la realización de búsquedas sistemáticas de bibliografía (A methodological proposal for the systematic literature review). WPOM-Work. Papers Oper. Manag. 1(2), 13–30 (2010)
Rousidis, D., et al.: Metadata for big data: a preliminary investigation of metadata quality issues in research data repositories. Inf. Serv. Use 34(3–4), 279–286 (2014)
Susan, S., Keshari, J.: Finding significant keywords for document databases by two-phase maximum entropy partitioning. Pattern Recognit. Lett. 125, 195–205 (2019)
Yadav, U., et al.: A novel approach for precise search results retrieval based on semantic web technologies. In: 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom) (2016)
Perkins, D., Jay, E., Tishman, S.: New conceptions of thinking: from ontology to education. Educ. Psychol. 28(1), 67–85 (1993). https://doi.org/10.1207/s15326985ep2801_6
Kurtz, M., Bollen, J.: Usage Bibliometrics, vol. 44. Information Today, Medford (2010)
Torres-Salinas, D., Jiménez-Contreras, E., Robinson-García, N.: Tendencias en mapas de la ciencia: co-uso de información científica como reflejo de los intereses de los investiga-dores (2014)
López-Nicolás, C., Meroño-Cerdán, Á.L.: Strategic knowledge management, innovation and performance. Int. J. Inf. Manag. 31(6), 502–509 (2011)
Konys, A.: Towards knowledge handling in ontology-based information extraction systems. Procedia Comput. Sci. 126, 2208–2218 (2018)
Zhang, G., et al.: VISAGE: a query interface for clinical research. Summit Transl. Bioinform. 2010, 76 (2010)
Damljanovic, D., Agatonovic, M., Cunningham, H.: FREyA: an interactive way of querying linked data using natural language. In: García-Castro, R., Fensel, D., Antoniou, G. (eds.) ESWC 2011. LNCS, vol. 7117, pp. 125–138. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-25953-1_11
Fan, J., Li, G., Zhou, L.: Interactive SQL query suggestion: making databases user-friendly. In: 2011 IEEE 27th International Conference on Data Engineering (2011)
Hiroko, K., et al.: Development of ontology for information literary. Procedia Comput. Sci. 60, 170–177 (2015)
Biletskiy, Y., et al.: Building a business domain meta-ontology for information pre-processing. Inf. Process. Lett. 138, 81–88 (2018)
Benedikt, M., Grau, B.C., Kostylev, E.V.: Logical foundations of information disclosure in ontology-based data integration. Artif. Intell. 262, 52–95 (2018)
Zhong, B., et al.: A scientometric analysis and critical review of construction related ontology research. Autom. Constr. 101, 17–31 (2019)
Macris, A.M., Georgakellos, D.A.: A new teaching tool in education for sustainable development: ontology-based knowledge networks for environmental training. J. Cleaner Prod. 14(9), 855–867 (2006). http://www.sciencedirect.com/science/article/pii/S0959652606000229https://doi.org/10.1016/j.jclepro.2005.12.009
Cassel, L.N., et al.: The computing ontology: application in education. ACM SIGCSE Bull. 39(4), 171–183 (2007)
Chi, N., Jin, Y., Hsieh, S.: Developing base domain ontology from a reference collection to aid information retrieval. Autom. Constr. 100, 180–189 (2019)
Du, J.T., Evans, N.: Academic users’ information searching on research topics: characteristics of research tasks and search strategies. J. Acad. Libr. 37(4), 299–306 (2011)
Qayyum, F., Afzal, M.T.: Identification of important citations by exploiting research articles’ metadata and cue-terms from content. Scientometrics 118(1), 21–43 (2019)
Nakashima, M., et al.: Browsing-based conceptual information retrieval incorporating dictionary term relations, keyword association, and a user’s interest. J. Am. Soc. Inf. Sci. Technol. 54(1), 16–28 (2003)
Porter, M.F.: An algorithm for suffix stripping. Program 14(3), 130–137 (1980)
Martini, B.: The data revolution. big data, open data, data infrastructures and their consequences. Reg. Stud. 50(3), 553–554 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Cano, L.D., Burgos, D., Fernández, C., Branch, J.W., Arango, M.D. (2019). A Novel Keyword Ontology Generator Method Tested on “Digital Transformation in Higher Education” Topic. In: Burgos, D., et al. Higher Education Learning Methodologies and Technologies Online. HELMeTO 2019. Communications in Computer and Information Science, vol 1091. Springer, Cham. https://doi.org/10.1007/978-3-030-31284-8_14
Download citation
DOI: https://doi.org/10.1007/978-3-030-31284-8_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-31283-1
Online ISBN: 978-3-030-31284-8
eBook Packages: Computer ScienceComputer Science (R0)