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Article
Segmenting Meetings into Agenda Items by Extracting Implicit Supervision from Human Note–Taking
Proceedings of the 2007 International Conference on Intelligent User Interfaces 2007
  • Satanjeev Banerjee, Carnegie Mellon University
  • Alexander I Rudnicky, Carnegie Mellon University
Date of Original Version
1-1-2007
Type
Conference Proceeding
Rights Management
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Abstract or Description
Splitting a meeting into segments such that each segment contains discussions on exactly one agenda item is useful for tasks such as retrieval and summarization of agenda item discussions. However, accurate topic segmentation of meetings is a difficult task. In this paper, we investigate the idea of acquiring implicit supervision from human meeting participants to solve the segmentation problem. Specifically we have implemented and tested a note taking interface that gives value to users by helping them organize and retrieve their notes easily, but that also extracts a segmentation of the meeting based on note taking behavior. We show that the segmentation so obtained achieves a Pk value of 0.212 which improves upon an unsupervised baseline by 45% relative, and compares favorably with a current state–of–the–art algorithm. Most importantly, we achieve this performance without any features or algorithms in the classic sense.
Citation Information
Satanjeev Banerjee and Alexander I Rudnicky. "Segmenting Meetings into Agenda Items by Extracting Implicit Supervision from Human Note–Taking" Proceedings of the 2007 International Conference on Intelligent User Interfaces 2007 (2007) p. 151 - 159
Available at: http://works.bepress.com/alexander_rudnicky/22/