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dc.contributor.authorWang, Xinen_US
dc.contributor.authorShilman, Michaelen_US
dc.contributor.authorRaghupathy, Sashien_US
dc.contributor.editorThomas Stahovich and Mario Costa Sousaen_US
dc.date.accessioned2014-01-27T19:17:07Z
dc.date.available2014-01-27T19:17:07Z
dc.date.issued2006en_US
dc.identifier.isbn3-905673-39-8en_US
dc.identifier.issn1812-3503en_US
dc.identifier.urihttp://dx.doi.org/10.2312/SBM/SBM06/043-050en_US
dc.description.abstractAnnotation is an integral part of reading, comprehending, commenting, and authoring notes and documents. In this paper we present a system for recognizing annotations in a flexible digital notebook that may contain a variety of content ranging from text, to images, to handwritten notes. To accomplish the recognition task in real-time makes the complicated annotation parsing problem more difficult. Our approach differs from previous approaches in several ways. First, our approach handles annotations on ink notes, which are significantly more ambiguous than annotations on printed documents and hence more difficult to recognize. Second, our approach is entirely learned from data, so it is easy to adapt to other scenarios. Third, our approach is more thoroughly evaluated than previous systems. On a test set of real user notes, the system has achieved an average recall of 0.9258 on all annotation types. Finally, the implementation of the approach will be commercially available as an API in the upcoming release of Windows® Vista® and Office 12®.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.7.m [Computing Methodologies]: Document and Text Processing; I.5.4 [Computing Technology]: Pattern Recognitionen_US
dc.titleParsing Ink Annotations on Heterogeneous Documentsen_US
dc.description.seriesinformationEurographics Workshop on Sketch-Based Interfaces and Modelingen_US


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