Communitysourcing Large-Scale Conference Scheduling

Cobi engages an entire academic community in planning a large-scale conference. Cobi elicits community members' preferences and constraints, and provides a scheduling tool empowering organizers to take informed actions toward improving the schedule.


Program committee members group papers sharing a common theme, providing affinity information between papers. This step provides mechanisms for clustering qualitative data given a small amount of experts' time. The collected data informs the initial session making process.

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Authors mark which other papers they find relevant to their paper, and which other papers they would personally like to attend. Cobi then encodes the responses into preferences and constraints, which reveals latent preferences and constraints previously not codified. This step provides fine-grained feedback to refine affinities and sessions.

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Cobi Scheduling Tool

Conference chairs use the web-based, visual scheduling interface that combines community input and constraint-solving intelligence. The tool enables chairs to resolve conflicts while considering other subjective factors, and to make informed improvements to the schedule.

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Conference attendees use the web app to decide where to spend their time during the conference by bookmarking favorite papers, getting social recommendations, and discovering the schedule. The recommendation engine takes authorsourcing data as initial input to bootstrap the algorithm, and improves as more attendees specify which papers they like.

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People in alphabetical order

Paul André (Facebook) Anant Bhardwaj (MIT CSAIL) Lydia Chilton (UW CSE) Steven P. Dow (CMU HCII) Juho Kim (MIT CSAIL) Robert C. Miller (MIT CSAIL) Haoqi Zhang (MIT CSAIL / Northwestern)



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