Attributes of images in describing tasks
Information Processing and Management: an International Journal
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Classification of user image descriptions
International Journal of Human-Computer Studies
The evolution of visual information retrieval
Journal of Information Science
Web Semantics: Science, Services and Agents on the World Wide Web
A hybrid ontology and visual-based retrieval model for cultural heritage multimedia collections
International Journal of Metadata, Semantics and Ontologies
Designing a thesaurus-based comparison search interface for linked cultural heritage sources
Proceedings of the 15th international conference on Intelligent user interfaces
MuseumFinland-Finnish museums on the semantic web
Web Semantics: Science, Services and Agents on the World Wide Web
A new model for semantic photograph description combining basic levels and user-assigned descriptors
Journal of Information Science
AAT-Taiwan: toward a multilingual access to cultural objects
ECDL'10 Proceedings of the 14th European conference on Research and advanced technology for digital libraries
Using ontological and document similarity to estimate museum exhibit relatedness
Journal on Computing and Cultural Heritage (JOCCH)
Visual Interface Design for Digital Cultural Heritage
Visual Interface Design for Digital Cultural Heritage
Using Ontologies to Reduce the Semantic Gap between Historians and Image Processing Algorithms
ICDAR '11 Proceedings of the 2011 International Conference on Document Analysis and Recognition
A case study for multilingual support: applying the AAT-thesaurus to TELDAP's multilingual project
ICADL'11 Proceedings of the 13th international conference on Asia-pacific digital libraries: for cultural heritage, knowledge dissemination, and future creation
Query terms for art images: a comparison of specialist and layperson terminology
BCS-HCI '11 Proceedings of the 25th BCS Conference on Human-Computer Interaction
A folksonomy-based recommender system for personalized access to digital artworks
Journal on Computing and Cultural Heritage (JOCCH)
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Information retrieval in a knowledge rich domain poses challenges that are different from other domains. The domain of fine arts and cultural heritage is an exemplar of such a domain. The many facets of, and complex interrelations between, works of fine art are not easily addressed by conventional keyword-based approaches or even by structured cataloguing systems. Information retrieval challenges in this domain include: the conversion of existing legacy data into knowledge representations that emulate the semantics of the domain's relationships; and easy access to a robust knowledge representation for users unfamiliar with query languages. Our research addresses aspects of both challenges as they are connected and may benefit from being addressed in conjunction. Based on a study on user preferences in art image search and a review of existing structured resources for cataloguing art and heritage information, we have developed two prototypes: Ontology Populator and Artfinder. The first prototype, Ontology Populator, is used to automatically enrich data akin to legacy data kept by heritage institutions and transform it into a knowledge base. The second prototype is a graphical query builder, Artfinder, which interacts with the knowledge base. The Artfinder interface, is constructed dynamically from the structure of the underlying knowledge. A task-based evaluation of Artfinder was carried out with 10 expert and 10 layperson evaluators. Participants reviewed the interface favourably and the evaluation also revealed potential for improvement. Artfinder and its “query logic,” perhaps is a semantically richer mode of accessing knowledge repositories, allowing for logically more complex queries than are currently supported outside the realm of dedicated query languages. We believe that domain experts and perhaps informed laypersons will benefit from this retrieval approach.