Paper: Models For Sentence Compression: A Comparison Across Domains Training Requirements And Evaluation Measures

ACL ID P06-1048
Title Models For Sentence Compression: A Comparison Across Domains Training Requirements And Evaluation Measures
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2006
Authors

Sentence compression is the task of pro- ducing a summary at the sentence level. This paper focuses on three aspects of this task which have not received de- tailed treatment in the literature: train- ing requirements, scalability, and auto- matic evaluation. We provide a novel com- parison between a supervised constituent- based and an weakly supervised word- based compression algorithm and exam- ine how these models port to different do- mains (written vs. spoken text). To achieve this, a human-authored compression cor- pus has been created and our study high- lights potential problems with the auto- matically gathered compression corpora currently used. Finally, we assess whether automatic evaluation measures can be used to determine compression quality.