Transductive learning over automatically detected themes for multi-document summarization

Massih-Reza Amini, Nicolas Usunier
2011 Proceedings of the 34th international ACM SIGIR conference on Research and development in Information - SIGIR '11  
We propose a new method for query-biased multi-document summarization, based on sentence extraction. The summary of multiple documents is created in two steps. Sentences are first clustered; where each cluster corresponds to one of the main themes present in the collection. Inside each theme, sentences are then ranked using a transductive learning-torank algorithm based on RankNet [2], in order to better identify those which are relevant to the query. The final summary contains the top-ranked
more » ... ntences of each theme. Our approach is validated on DUC 2006 and DUC 2007 datasets.
doi:10.1145/2009916.2010115 dblp:conf/sigir/AminiU11 fatcat:euoccg5iirgsnigtpheeaxz2jm