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Details

Autor(en) / Beteiligte
Titel
Supporting Knowledge Creation through HAS: The Hyperknowledge Annotation System
Ist Teil von
  • 2018 IEEE International Symposium on Multimedia (ISM), 2018, p.239-246
Ort / Verlag
IEEE
Erscheinungsjahr
2018
Quelle
IEEE Electronic Library (IEL)
Beschreibungen/Notizen
  • Annotation systems provide services that vary from adding simple information for signifying content of interest, to indicate patterns in documents for creating statistical models and applying machine learning techniques. In this paper, we argue that AI mechanisms should be part of the annotation process to collaborate with annotation systems' end users (i.e. annotators) as oppose to be just an outcome from annotators' work. Indeed, current systems do not delve into AI aspects to support the annotation process, lacking features that we argue as essential in annotation systems. That is, collaboration between annotators and AI, collaborative knowledge curation by extracting and structuring knowledge from annotations considering the context of annotation anchors (i.e. area that was selected to create an annotation and comprises the content of interest). To illustrate the gains of this approach, we present HAS, the Hyperknowledge Annotation System. HAS allows one to annotate multimedia content (e.g., text, image, and video) and its tight integration with AI-based services enables the extraction of additional semantic information from the annotated content. In our approach, both the annotation and the information extracted from the content are structured using the hyperknowledge conceptual model, which promotes the use of the spatiotemporal query capabilities of this model for retrieving annotations based on semantic queries. We argue that integrating AI-based services and using the hyperknowledge model for knowledge structuring leverage multimedia annotation systems, enabling the development of novel use cases.
Sprache
Englisch
Identifikatoren
DOI: 10.1109/ISM.2018.00034
Titel-ID: cdi_ieee_primary_8603296

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