Paper: Detecting Shifts In News Stories For Paragraph Extraction

ACL ID C02-1085
Title Detecting Shifts In News Stories For Paragraph Extraction
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2002
Authors

For multi-document summarization where docu- ments are collected over an extended period of time, the subject in a document changes over time. This paper focuses onsubject shiftandpresents amethod for extracting key paragraphs from documents that discuss the same event. Our extraction method uses the results of event tracking which starts from a few sample documents and finds all subsequent docu- ments that discuss the same event. The method was tested on the TDT1corpus, andthe result shows the effectiveness of the method.