Summary of Summary Paper Kupiec, Pedersen, and Chen, SIGIR 94
To summarize is to reduce in complexity, and hence in length, while retaining some of the essential qualities of the original.
This paper focuses on document extracts, a particular kind of computed document summary.
Document extracts consisting of roughly 20% of the original can be as informative as the full text of a document, which suggests that even shorter extracts may be useful indictive summaries.
The trends in our results are in agreement with those of Edmunson who used a subjectively weighted combination of features as opposed to training the feature weights using a corpus.
We have developed a trainable summarizer program that is grounded in a solid statistical framework.