Article thumbnail

E.: Machine Learning of Generic and User-Focused Summarization. Arxiv preprint cs (CL/9811006

By Eric Bloedorn

Abstract

A key problem in text summarization is finding a salience function which determines what information in the source should be included in the summary. This paper describes the use of machine learning on a training corpus of documents and their abstracts to discover salience functions which describe what combination of features is optimal for a given summarization task. The method addresses both "generic " and user-focused summaries

Year: 1998
OAI identifier: oai:CiteSeerX.psu:10.1.1.331.5751
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://www.aaai.org/Papers/AAA... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.