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Abstract

Semantic annotation of images is an important step to support semantic information extraction and retrieval. However, in a multi-annotator environment, various types of conflicts such as converting, merging, and inference conflicts could arise during the annotation. We devised conflict detection patterns based on different data, ontology at different inference levels and proposed the corresponding automatic conflict resolution strategies. We also constructed a simple annotator model to decide whether to trust a given piece of annotation from a given annotator. Finally, we conducted experiments to compare the performance of the automatic conflict resolution approaches during the annotation of images in the celebrity domain by 62 annotators. The experiments showed that the proposed method improved 3/4 annotation accuracy with respect to a naïve annotation system.

Date

26.12.2007 18:29:29

Source

Information processing and management. 42(2006) no.4, S.1030-1055

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Source

Knowledge organization for a global learning society: Proceedings of the 9th International ISKO Conference, 4-7 July 2006, Vienna, Austria. Hrsg.: G. Budin, C. Swertz u. K. Mitgutsch

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Source

Knowledge organization. 32(2005) no.4, S.141-142

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Date

4. 6.2010 19:51:42

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Source

Knowledge organization. 36(2009) no.4, S.200-213