TY - GEN
T1 - From assets to stories via the Google Cultural Institute Platform
AU - Seales, W. Brent
AU - Crossan, Steve
AU - Yoshitake, Mark
AU - Girgin, Sertan
PY - 2013
Y1 - 2013
N2 - The Google Cultural Institute Platform1 is a large-scale system for ingesting, archiving, organizing, and interacting with digital assets of cultural material. This paper explains the components through which the platform contextualizes individual assets in order to enable storytelling. Contextual-ization is an inverse problem: given assets that are instances of cultural material, infer their precise context and use that as a way to support the storytelling process. The approach is based on three components: extraction, knowledge, and scale. Extraction is the inference of context from two sources of information: explicitly provided metadata, and automatically extracted features. Knowledge is the use of a large reference fact database for further contextualizing an asset based on its descriptors. And scale, achieved through global self-serve, enables massively expanded coverage of the knowledge database and crowdsource potential for metadata refinement. Together these components sustain a storytelling framework and a compelling user experience that has the potential to become the largest repository of cultural information and coherent narrative in history.
AB - The Google Cultural Institute Platform1 is a large-scale system for ingesting, archiving, organizing, and interacting with digital assets of cultural material. This paper explains the components through which the platform contextualizes individual assets in order to enable storytelling. Contextual-ization is an inverse problem: given assets that are instances of cultural material, infer their precise context and use that as a way to support the storytelling process. The approach is based on three components: extraction, knowledge, and scale. Extraction is the inference of context from two sources of information: explicitly provided metadata, and automatically extracted features. Knowledge is the use of a large reference fact database for further contextualizing an asset based on its descriptors. And scale, achieved through global self-serve, enables massively expanded coverage of the knowledge database and crowdsource potential for metadata refinement. Together these components sustain a storytelling framework and a compelling user experience that has the potential to become the largest repository of cultural information and coherent narrative in history.
KW - image analysis
KW - knowledge management
KW - semantic web
KW - text analysis
UR - http://www.scopus.com/inward/record.url?scp=84893221366&partnerID=8YFLogxK
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U2 - 10.1109/BigData.2013.6691673
DO - 10.1109/BigData.2013.6691673
M3 - Conference contribution
AN - SCOPUS:84893221366
SN - 9781479912926
T3 - Proceedings - 2013 IEEE International Conference on Big Data, Big Data 2013
SP - 71
EP - 76
BT - Proceedings - 2013 IEEE International Conference on Big Data, Big Data 2013
T2 - 2013 IEEE International Conference on Big Data, Big Data 2013
Y2 - 6 October 2013 through 9 October 2013
ER -