Comparison of Data Sources for Automatic Annotation of Educational Videos
Abstract
The volume of the educational video repositories has rapidly increased as the creation of new digital resources is facilited. However, such repositories need better indexing and searching engines. Users find it difficult to find useful information when educational videos has poor quality metadata. The proccess of adding new descriptors to videos is called annontation. In this work, we will discuss how the information extracted from educational videos influence the automatic semantic annotation task. We will present an comparative analysis among these information sources and we will demonstrate which information sources are most useful for annontation task.
Keywords:
educational videos, automatic annotation, data sources, indexing, searching
References
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de Oliveira, F. K., Santana, J. R., and de Oliveira Pontes, M. G. (2010). O vídeo como ferramenta educacional a partir de multiplas plataformas. In Brazilian Symposium on Computers in Education (Simposio Brasileiro de Informática na Educação-SBIE), volume 1.
Gravier, G., Jones, G.F., Larson, M., and Ordelman, R. (2015). Overview of the 2015 workshop on speech, language and audio in multimedia. In Proceedings of the 23rd ACM international conference on Multimedia, pages 1347–1348. ACM.
Grünewald, F. and Meinel, C. (2015). Implementation and evaluation of digital e-lecture annotation in learning groups to foster active learning. IEEE Transactions on Learning Technologies, 8(3):286–298.
Gupta, Y., Saini, A., and Saxena, A. (2015). A new fuzzy logic based ranking function for efficient information retrieval system. Expert Systems with Applications, 42(3):1223–1234.
Habibian, A., Mensink, T., and Snoek, C.G. (2015). Discovering semantic vocabularies for cross-media retrieval. In Proceedings of the 5th ACM on International Conference on Multimedia Retrieval, pages 131–138. ACM.
Hauptmann, A.G., Jin, R., and Ng, T.D. (2003). Video retrieval using speech and image information. In Electronic Imaging 2003, pages 148–159. International Society for Optics and Photonics.
Jiang, Y.-G., Bhattacharya, S., Chang, S.-F., and Shah, M. (2013). High-level event recognition in unconstrained videos. International journal of multimedia information retrieval, 2(2):73–101.
Maynard, D. and Hare, J. (2015). Entity-based opinion mining from text and multimedia. In Advances in Social Media Analysis, pages 65–86. Springer.
Medeiros, S.F. d.L. and Pansanato, L. (2015). Estudo das preferências de alunos e professores sobre videoaula para identificar requisitos de software para ferramentas de produção. In Brazilian Symposium on Computers in Education (Simpósio Brasileiro de Informática na Educação - SBIE), volume 26, page 219.
Mendes, P.N., Jakob, M., García-Silva, A., and Bizer, C. (2011). Dbpedia spotlight: shedding light on the web of documents. In Proceedings of the 7th international conference on semantics systems, pages 1–8. ACM.
Qazi, A. and Goudar, R. (2016). Emerging trends in reducing semantic gap towards multimedia access: A comprehensive survey. Indian Journal of Science and Technology, 9(30).
Raimond, Y. and Lowis, C. (2012). Automated interlinking of speech radio archives. Linked Data on the Web (LDOW’16).
Taskiran, C.M., Pizlo, Z., Amir, A., Ponceleon, D., and Delp, E.J. (2006). Automated video program summarization using speech transcripts. IEEE Transactions on Multimedia, 8(4):775–791.
Yang, H. and Meinel, C. (2014). Content-based lecture video retrieval using speech and video text information. IEEE Transactions on Learning Technologies, 7(2):142–154.
Zhao, B., Xu, S., Lin, S., Luo, X., and Duan, L. (2015). A new visual navigation system for exploring biomedical open educational resource (OER) videos. Journal of the American Medical Informatics Association, 23(e1):e34–e41.
Published
2017-10-30
How to Cite
SOUZA, Jairo Francisco de; GOMES JR., Jorão; BARRÉRE, Eduardo.
Comparison of Data Sources for Automatic Annotation of Educational Videos. In: BRAZILIAN SYMPOSIUM ON COMPUTERS IN EDUCATION (SBIE), 28. , 2017, Recife/PE.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2017
.
p. 1127-1136.
DOI: https://doi.org/10.5753/cbie.sbie.2017.1127.
