A context-based algorithm for annotating educational content with Linked Data
In this paper we present an approach for annotating and enriching educational contents modeled as Learning Fruits (LFs). LFs are web books described in XML files and created to make more dynamic and flexible the learning process. A way to reduce the cost of creating a LF is to complete its content with information available in the Web. The solution described in this paper combines syntactic and semantic analysis techniques to enrich and annotate the LFs with relevant and reliable data retrieved from the DBpedia repository
keywords: semantic annotation, linked data
Publication: Congress
1624015021368
June 18, 2021
/research/publications/a-context-based-algorithm-for-annotating-educational-content-with-linked-data
In this paper we present an approach for annotating and enriching educational contents modeled as Learning Fruits (LFs). LFs are web books described in XML files and created to make more dynamic and flexible the learning process. A way to reduce the cost of creating a LF is to complete its content with information available in the Web. The solution described in this paper combines syntactic and semantic analysis techniques to enrich and annotate the LFs with relevant and reliable data retrieved from the DBpedia repository - Estefanía Otero-García, Juan C. Vidal, Manuel Lama, Alberto Bugarín and José E. Domenech
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