Semantic Annotation Automatic of Curriculum Lattes Using Linked Open Data

Abstract The Semantic Web has the purpose of optimizing document recovery, where these documents received synonyms, allowing people and machines to understand the meaning of one information. The semantic annotation entity is the path to promote the semantic in documents. This paper has an objective to build an outline with the Semantic Web concepts that allow to automatically annotate entities in the Lattes Curriculum based on Linked Open Data (LOD), which store terms and expressions’ meaning. The problem addressed in this research is based on what of the Semantic Web concepts can contribute to the Automatic Semantic Annotation Entities of the Lattes Curriculum using Linked Open Data. During the literature review the concepts, tools and technologies related to the theme were presented. The application of these concepts allowed the creation of the Semantic Web Lattes System. An empirical study was conducted with the objective of identifying an Extraction Tool Entity further Effective. The system allows importing the XML curricula in the Lattes Platform, annotates automatically the available data using the open databases and allows to run semantic queries.