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Recommending Metadata Contents for Learning Objects Through Linked Data

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Highlights in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection (PAAMS 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1472))

Abstract

Attach metadata to digital objects effectively underlies the development of high-quality services in systems. This work explores how the metadata of a learning object represented as linked data, in a brand new repository, can be a facilitator to a more complete catalog and search with contents recommendations. The proposed approach underlies in DBpedia Spotlight for unstructured text annotation to deliver recommendations at the learning object cataloging phase and GEMET, a marine domain thesaurus, to expand marine searching terms. Each learning object is described with OBAA metadata as a set of triples stored in Resource Description Framework format to deliver interoperability and Linked Data compatibility.

This work is financed by the FEDER in 85% and by regional funds in 15%, through the Operational Program Azores 2020, within the scope of the SEA-THINGS Learning Objects to Promote Ocean Literacy project ACORES-01-0145-FEDER-000110. This study was also supported in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES) - Finance Code 001. This work was partially funded by FEDER funds through the Operational Programme for Competitiveness Factors - COMPETE and by National Funds through FCT - Foundation for Science and Technology under the UID/BIA/50027/2020 and POCI-01-0145-FEDER-006821, by funding the CIBIO/InBIO.

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Notes

  1. 1.

    https://www.w3.org/wiki/SweoIG/TaskForces/CommunityProjects/LinkingOpenData.

  2. 2.

    https://fgf.uac.pt/en/content/sea-things-objetos-de-aprendizagem-para-promover-literacia-oceanica.

  3. 3.

    http://creativecommons.org/licenses/by-sa/4.0/.

  4. 4.

    http://creativecommons.org/licenses/by-nc-sa/4.0/.

  5. 5.

    https://www.eionet.europa.eu/gemet/en/exports/rdf/latest.

  6. 6.

    http://repositorio.uac.pt/oaiextended/request?verb=ListRecords&metadataPrefix=oai_dc&set=com_10400.3_10 Accessed in 2021/05/25.

References

  1. Allam, Z., Dhunny, Z.A.: On big data, artificial intelligence and smart cities. Cities 89, 80–91 (2019)

    Article  Google Scholar 

  2. Behr, A., Primo, T.T., Vicari, R.: Obaa-leme: a learning object metadata content editor supported by application profiles and educational metadata ontologies. In: Anais dos Workshops do Congresso Brasileiro de Informática na Educação, vol. 3, p. 455 (2014)

    Google Scholar 

  3. Behr, A.R.: Uma abordagem para promover reuso e processamento de inferências em ontologias de metadados educacionais. Master’s Thesis (2016)

    Google Scholar 

  4. Bizer, C., Heath, T., Berners-Lee, T.: Linked data: the story so far. In: Semantic Services, Interoperability and Web Applications: Emerging Concepts, pp. 205–227. IGI global (2011)

    Google Scholar 

  5. Daiber, J., Jakob, M., Hokamp, C., Mendes, P.N.: Improving efficiency and accuracy in multilingual entity extraction. In: Proceedings of the 9th International Conference on Semantic Systems (I-Semantics) (2013)

    Google Scholar 

  6. Di Noia, T., Magarelli, C., Maurino, A., Palmonari, M., Rula, A.: Using ontology-based data summarization to develop semantics-aware recommender systems. In: Gangemi, A., et al. (eds.) ESWC 2018. LNCS, vol. 10843, pp. 128–144. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93417-4_9

  7. Egyedi, A.L., et al.: Embracing semantic technology for better metadata authoring in biomedicine. In: (SWAT4LS) (2017)

    Google Scholar 

  8. Gluz, J.C., Vicari, R.M., Passerino, L.M.: An agent-based infrastructure for the support of learning objects life-cycle. In: Cerri, S.A., Clancey, W.J., Papadourakis, G., Panourgia, K. (eds.) ITS 2012. LNCS, vol. 7315, pp. 696–698. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-30950-2_126

    Chapter  Google Scholar 

  9. Govathoti, S., Babu, M.P.: An implementation of a new framework for automatic generation of ontology and RDF to real time web and journal data. Int. J. Comput. Sci. Inf. Secur. (IJCSIS) 16(1) (2018)

    Google Scholar 

  10. Hitzler, P., Janowicz, K.: Linked data, big data, and the 4th paradigm. Semantic Web 4(3), 233–235 (2013)

    Article  Google Scholar 

  11. Medina, M.A., Sánchez, J.A., Cervantes, O., Benitez, A., de la Calleja, J.: LOD4AIR: a strategy to produce and consume linked open data from OAI-PMH repositories. In: 2017 International Conference on Electronics, Communications and Computers (CONIELECOMP), pp. 1–8. IEEE (2017)

    Google Scholar 

  12. Nahhas, S., Bamasag, O., Khemakhem, M., Bajnaid, N.: Added values of linked data in education: a survey and roadmap. Computers 7(3), 45 (2018)

    Article  Google Scholar 

  13. Natarajan, S., Vairavasundaram, S., Natarajan, S., Gandomi, A.H.: Resolving data sparsity and cold start problem in collaborative filtering recommender system using linked open data. Expert Syst. with Appl. 149, 113248 (2020)

    Article  Google Scholar 

  14. Pereira, C.K., Campos, F., Ströele, V., David, J.M.N., Braga, R.: Broad-RSI-educational recommender system using social networks interactions and linked data. J. Internet Serv. Appl. 9(1), 1–28 (2018)

    Article  Google Scholar 

  15. Pereira, C.K., Siqueira, S.W.M., Nunes, B.P., Dietze, S.: Linked data in education: a survey and a synthesis of actual research and future challenges. IEEE Trans. Learn. Technol. 11(3), 400–412 (2017)

    Article  Google Scholar 

  16. Shadbolt, N., Hall, W., Berners-Lee, T.: The semantic web revisited. Intell. Syst. IEEE 21(3), 96–101 (2006)

    Article  Google Scholar 

  17. Tavakoli, M., Elias, M., Kismihók, G., Auer, S.: Metadata analysis of open educational resources. In: LAK21: 11th International Learning Analytics and Knowledge Conference, pp. 626–631 (2021)

    Google Scholar 

  18. Vagliano, I., Monti, D., Morisio, M.: Semrevrec, : A recommender system based on user reviews and linked data. In: RecSys Posters (2017)

    Google Scholar 

  19. Vagliano, I., Monti, D., Scherp, A., Morisio, M.: Content recommendation through semantic annotation of user reviews and linked data. In: Proceedings of the Knowledge Capture Conference, pp. 1–4 (2017)

    Google Scholar 

  20. Vicari, R.M., Ribeiro, A., da Silva, J.M.C., Santos, E.R., Primo, T., Bez, M.: Brazilian proposal for agent-based learning objects metadata standard - OBAA. In: Sánchez-Alonso, S., Athanasiadis, I.N. (eds.) MTSR 2010. CCIS, vol. 108, pp. 300–311. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-16552-8_27

    Chapter  Google Scholar 

  21. Wiley, D.A.: Learning object design and sequencing theory. Ph.D. Thesis, Brigham Young University (2000)

    Google Scholar 

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Author information

Authors and Affiliations

  1. FCT, University of the Azores, Ponta Delgada, Portugal

    André Behr, Armando Mendes, José Cascalho, Hélia Guerra, Ana Costa, Manuela Parente & Andrea Botelho

  2. GRIA and LIACC, Ponta Delgada, Portugal

    Armando Mendes & José Cascalho

  3. NIDeS and Centro Algoritmi, Ponta Delgada, Portugal

    Hélia Guerra

  4. CIBIO and InBIO, Ponta Delgada, Portugal

    Ana Costa, Manuela Parente & Andrea Botelho

  5. ISEL and GuIAA, Lisbon, Portugal

    Paulo Trigo

  6. Federal University of Rio Grande do Sul, Porto Alegre, Brazil

    Rosa Vicari

Authors
  1. André Behr
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  2. Armando Mendes
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  3. Paulo Trigo
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  4. José Cascalho
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  5. Hélia Guerra
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  6. Ana Costa
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  7. Manuela Parente
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  8. Andrea Botelho
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  9. Rosa Vicari
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Editor information

Editors and Affiliations

  1. University of Salamanca, Salamanca, Spain

    Fernando De La Prieta

  2. German University in Cairo, New Cairo City, Egypt

    Alia El Bolock

  3. University of Minho, Braga, Portugal

    Dalila Durães

  4. Polytechnic Institute of Porto, ISEP, Porto, Portugal

    João Carneiro

  5. National Laboratory of Energy and Geology, Lisbon, Portugal

    Fernando Lopes

  6. Polytechnic University of Valencia, Valencia, Valencia, Spain

    Vicente Julian

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Behr, A. et al. (2021). Recommending Metadata Contents for Learning Objects Through Linked Data. In: De La Prieta, F., El Bolock, A., Durães, D., Carneiro, J., Lopes, F., Julian, V. (eds) Highlights in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection. PAAMS 2021. Communications in Computer and Information Science, vol 1472. Springer, Cham. https://doi.org/10.1007/978-3-030-85710-3_10

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  • DOI: https://doi.org/10.1007/978-3-030-85710-3_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-85709-7

  • Online ISBN: 978-3-030-85710-3

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