Most of the semantic content available has been generated automatically by using annotation services for existing content. 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 an end-user study to evaluate its acceptance by and usability for non-expert users. This paper presents the results of this user study and discusses the lessons learned about both the semantic enrichment process and our methodology of exposing non-experts to semantic enrichment. © 2012 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Hinze, A., Heese, R., Luczak-Rösch, M., & Paschke, A. (2012). Semantic enrichment by non-experts: Usability of manual annotation tools. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7649 LNCS, pp. 165–181). Springer Verlag. https://doi.org/10.1007/978-3-642-35176-1_11
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