Date of Original Version
Proceedings of the 2007 International Conference on Intelligent User Interfaces 2007. pp. 151-159.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for proﬁt or commercial advantage and that copies bear this notice and the full citation on the ﬁrst page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior speciﬁc permission and/or a fee.
Abstract or Table of Contents
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.