Raymond F. Boyce, Donald D. Chamberlin, et al.
CACM
We present a multi-document summarizer, MEAD, which generates summaries using cluster centroids produced by a topic detection and tracking system. We describe two new techniques, a centroid-based summarizer, and an evaluation scheme based on sentence utility and subsumption. We have applied this evaluation to both single and multiple document summaries. Finally, we describe two user studies that test our models of multi-document summarization. © 2003 Elsevier Ltd. All rights reserved.
Raymond F. Boyce, Donald D. Chamberlin, et al.
CACM
Lerong Cheng, Jinjun Xiong, et al.
ASP-DAC 2008
Minkyong Kim, Zhen Liu, et al.
INFOCOM 2008
Alfonso P. Cardenas, Larry F. Bowman, et al.
ACM Annual Conference 1975