Paper: FastSum: Fast and Accurate Query-based Multi-document Summarization

ACL ID P08-2052
Title FastSum: Fast and Accurate Query-based Multi-document Summarization
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008
Authors

Wepresentafastquery-basedmulti-document summarizer called FastSum based solely on word-frequency features of clusters, docu- ments and topics. Summary sentences are ranked by a regression SVM. The summa- rizer does not use any expensive NLP tech- niques such as parsing, tagging of names or even part of speech information. Still, the achieved accuracy is comparable to the best systems presented in recent academic com- petitions (i.e., Document Understanding Con- ference (DUC)). Because of a detailed fea- ture analysis using Least Angle Regression (LARS), FastSum can rely on a minimal set of featuresleading tofastprocessingtimes: 1250 news documents in 60 seconds.