Full text
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| Author(s): |
Marcos Vinícius Macêdo Borges
Total Authors: 1
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| Document type: | Master's Dissertation |
| Press: | Campinas, SP. |
| Institution: | Universidade Estadual de Campinas (UNICAMP). Instituto de Computação |
| Defense date: | 2021-03-10 |
| Examining board members: |
Julio Cesar dos Reis;
Flavia Linhalis;
Diego Addan Gonçalves
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| Advisor: | Julio Cesar dos Reis |
| Abstract | |
Learning support systems explore several audio-visual resources to consider individual needs and learning styles aiming to stimulate learning experiences. However, the large amount of online educational content in di?erent formats and the possibility of making them available in a fragmented way turns di?cult the tasks of accessing these resources and understanding the concepts under study. Although literature has proposed approachestoexploreexplicitsemanticrepresentationthroughartifactssuchasontologies in learning support systems, this research line still requires further investigation e?orts. In this MS.c. dissertation, we propose a method for recommending educational content by exploring the use of semantic annotations over textual transcriptions from video lectures. Our investigation addresses the di?culties in extracting entities from natural language texts in subtitles of videos. Our work studies how to re?ne concepts in a domain ontology to support semantic annotation of video lecture subtitles. We report on the design of a video lecture recommendation system which explores the extracted semantic annotations. Our solution explored semantically annotated videos with an ontology in the Computer Science domain. Obtained results indicate our recommendation mechanism is suited to ?lter relevant video content in di?erent use scenarios (AU) | |
| FAPESP's process: | 18/00313-2 - Semantic annotations for the recommendation of educational contents |
| Grantee: | Marcos Vinicius Macêdo Borges |
| Support Opportunities: | Scholarships in Brazil - Master |