Kurator: Using The Crowd to Help Families With Personal Curation Tasks

TitleKurator: Using The Crowd to Help Families With Personal Curation Tasks
Publication TypeConference Paper
Year of Publication2017
AuthorsMerritt, D, Jones, J, Ackerman, MS, Lasecki, WS
Conference NameProceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing
Pagination1835–1849
Keywordscrowdsourcing, curation, digital audio, digital curation, hybrid intelligence, mixed-expertise, personal curation
Abstract

People capture photos, audio recordings, video, and more on a daily basis, but organizing all these digital artifacts quickly becomes a daunting task. Automated solutions struggle to help us manage this data because they cannot understand its meaning. In this paper, we introduce Kurator, a hybrid intelligence system leveraging mixed-expertise crowds to help families curate their personal digital content. Kurator produces a refined set of content via a combination of automated systems able to scale to large data sets and human crowds able to understand the data. Our results with 5 families show that Kurator can reduce the amount of effort needed to find meaningful memories within a large collection. This work also suggests that crowdsourcing can be used effectively even in domains where personal preference is key to accurately solving the task.

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