Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/16976
Title: Timely and nonintrusive active document annotation via adaptive information extraction
Authors: Ciravegna, Fabio
Dingli, Alexiei
Petrelli, Daniela
Wilks, Yorick
Keywords: Semantic Web
Information retrieval -- Automation
Corpora (Linguistics)
Natural language processing (Computer science)
Issue Date: 2002
Publisher: IOS Press
Citation: Ciravegna, F., Dingli, A., Petrelli, D., & Wilks, Y. (2002). Timely and nonintrusive active document annotation via adaptive information extraction. 15th European Conference on Artificial Intelligence (ECAI 2002), Lyon. 1-7.
Abstract: The process of document annotation for the Semantic Web is complex and time consuming, as it requires a great deal of manual annotation. Information extraction from texts (IE) is a technology used by some of the most recent systems for actively supporting users in the process and reducing the burden of annotation. The integration of IE systems in annotation tools is quite a new development and in our opinion there is still the necessity of thinking the impact of the IE system in the process of annotation. In this paper we discuss two main requirements for active annotation: timeliness and tuning of intrusiveness. Then we present and discuss a model of interaction that addresses the two issues and Melita, an annotation framework that implements such methodology.
Description: The current work has been carried on in the framework of the AKT project (Advanced Knowledge Technologies, http://www.aktors.org), an Interdisciplinary Research Collaboration (IRC) sponsored by the UK Engineering and Physical Sciences Research Council (grant GR/N15764/01). AKT involves the Universities of Aberdeen, Edinburgh, Sheffield, Southampton and the Open University (www.aktors.org). AKT is a multimillion pound six year research project that started in 2000.
URI: https://www.um.edu.mt/library/oar//handle/123456789/16976
Appears in Collections:Scholarly Works - FacICTAI

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