Finding Weather Photos: Community-Supervised Methods For Editorial Curation Of Online Sources
CSCW '16: Computer Supported Cooperative Work and Social Computing San Francisco California USA February, 2016(2016)
摘要
There are many cues that can be used to curate media from social networking websites. Beyond metadata, group behavior provide a strong community-based signal for surfacing images, which we show in a user-defined curatorial task. In a departure from mirco-task crowdwork, we observe that the curation inherent in online photo communities guides the discoverability and consumption of the media, which in turn provides a strong signal that can be used in new editorial tasks in a community-supervised manner. We use this approach in tandem with other more conventional multimedia methods (i.e. computer vision and contextual metadata) to form a broad multimodal approach to retrieval and recommendation. We present a large-scale system implementation on a real-world curative task for weather images on a web-scale dataset. Finally, we conduct an evaluation of this system using professional editors and find substantial improvements in editorial efficiency.
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关键词
Community,Learning,Weather,Editorial,Retrieval,Social,Content Analysis,Human Centered Computing,Community Supervised,Flickr,Photos
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