Semantic annotation of digital documents is typically done at meta-data level. However, for fine-grained access semantic enrichment of text elements or passages is needed. Automatic annotation is not of sufficient quality to enable focused search and retrieval: either too many or too few terms are semantically annotated. User-defined semantic enrichment allows for a more targeted approach. We developed a tool for semantic annotation of digital documents and conducted a number of studies to evaluate its acceptance by and usability for non-expert users. This paper discusses the lessons learned about both the semantic enrichment process and our methodology of exposing non-experts to semantic enrichment. © 2012 Springer-Verlag.
CITATION STYLE
Hinze, A., Heese, R., Schlegel, A., & Luczak-Rösch, M. (2012). User-defined semantic enrichment of full-text documents: Experiences and lessons learned. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7489 LNCS, pp. 209–214). https://doi.org/10.1007/978-3-642-33290-6_23
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