Paper: Sentence Reduction For Automatic Text Summarization

ACL ID A00-1043
Title Sentence Reduction For Automatic Text Summarization
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2000
Authors

We present a novel sentence reduction system for automatically removing extraneous phrases from sentences that are extracted from a document for summarization purpose. The system uses multiple sources of knowledge to decide which phrases in an extracted sentence can be removed, including syn- tactic knowledge, context information, and statistics computed from a corpus which consists of examples written by human professionals. Reduction can sig- nificantly improve the conciseness of automatic sum- maries. 1 Motivation Current automatic summarizers usually rely on sen- tence extraction to produce summaries. Human pro- fessionals also often reuse the input documents to generate summaries; however, rather than simply extracting sentences and stringing them together, as most current summarizers...