Paper: Multi-Document Summarization Using A* Search and Discriminative Learning

ACL ID D10-1047
Title Multi-Document Summarization Using A* Search and Discriminative Learning
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2010
Authors

In this paper we address two key challenges for extractive multi-document summarization: the search problem of finding the best scoring summary and the training problem of learn- ing the best model parameters. We propose an A* search algorithm to find the best extractive summary up to a given length, which is both optimal and efficient to run. Further, we pro- pose a discriminative training algorithm which directly maximises the quality of the best sum- mary, rather than assuming a sentence-level decomposition as in earlier work. Our ap- proach leads to significantly better results than earlier techniques across a number of evalua- tion metrics.