Paper: Extracting Important Sentences With Support Vector Machines

ACL ID C02-1053
Title Extracting Important Sentences With Support Vector Machines
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2002

Extractingsentencesthatcontainimportantin- formation from a document is a form of text summarization. The technique is the key tothe automatic generation of summaries similar to those written by humans. To achieve such ex- traction, it is important to be able to integrate heterogeneous pieces of information. One ap- proach, parameter tuning by machine learning, has been attracting a lot of attention. This pa- per proposes a method of sentence extraction based on Support Vector Machines (SVMs). To confirm the method’s performance, we conduct experiments that compare our method to three existing methods. Results on the Text Summa- rization Challenge (TSC) corpus show that our method offers the highest accuracy. Moreover, we clarify the different features effective for ex- tracting di...