Content-based annotation and classification framework: a general multi-purpose approach

Authors:
Michal Batko;Jan Botorek;Petra Budikova;Pavel Zezula
Affiliations:
Masaryk University, Brno, Czech Republic;Masaryk University, Brno, Czech Republic;Masaryk University, Brno, Czech Republic;Masaryk University, Brno, Czech Republic
Venue:
Proceedings of the 17th International Database Engineering & Applications Symposium
Year:
2013

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Abstract

Unprecedented amounts of digital data are becoming available nowadays, but frequently the data lack some semantic information necessary to effectively organize these resources. For images in particular, textual annotations that represent the semantics are highly desirable. Only a small percentage of images is created with reliable annotations, therefore a lot of effort is being invested into automatic image annotation. In this paper, we address the annotation problem from a general perspective and introduce a new annotation model that is applicable to many text assignment problems. We also provide experimental results from several implemented instances of our model.