Advances in Automatic Text Summarization

It has been said for decades (if not centuries) that more and more information is becoming available and that tools are needed to handle it. Only recently, however, does it seem that a sufficient quantity of this information is electronically available to produce a widespread need for automatic summarization. Consequently, this research area has enjoyed a resurgence of interest in the past few years, as illustrated by a 1997 ACL Workshop, a 1998 AAAI Spring Symposium and in the same year SUMMAC: a TREC-like TIPSTER-funded summarization evaluation conference. Not unexpectedly, there is now a book to add to this list: Advances in Automatic Summarization, a collection of papers edited by Inderjeet Mani and Mark T. Maybury and published by The MIT Press. Half of it is a historical record: thirteen previously published papers, including classics such as Luhn's 1958 word-counting sentence-extraction paper, Edmundson's 1969 use of cue words and phrases, and Kupiec, Pedersen, and Chen's 1995 trained summarizer. The other half of the book holds new papers, which attempt to cover current issues and point to future trends. It starts with a paper by Karen Sp~irck Jones, which acts as an overall introduction. In it, the summarization process and the uses of summaries are broken down into their constituent parts and each of these is discussed (it reminded me of a much earlier Sp~rck Jones paper on categorization [1970]). Despite its comprehensiveness and authority, I must confess to finding this opener heavy going at times. The rest of the papers are grouped into six sections, each of which is prefaced with two or three well-written pages from the editors. These introductions contain valuable commentary on the coming papers--even pointing out a possible flaw in the evaluation part of one. The opening section holds three papers on so-called classical approaches. Here one finds the oft-cited papers of Luhn, Edmundson, and Pollock and Zamora. As a package, these papers provide a novice with a good idea of how basic summarization works. My only quibble was in their reproduction. In Luhn's paper, an article from Scientific American is summarized and it would have been beneficial to have this included in the book as well. Some of the figures in another paper contained very small fonts and were hard to read; fixing this for a future print run is probably worth thinking about. The next section holds papers on corpus-based approaches to summarization, starting with Kupiec et al.'s paper about a summarizer trained on an existing corpus of manually abstracted documents. Two new papers building upon the Kupiec et al. work follow this. Exploiting the discourse structure of a document is the topic of the next section. Of the five papers here, I thought Daniel Marcu's was the best, nicely describing summarization work so far and then clearly explaining his system, which is based on Rhetorical Structure Theory. The following section on knowledge-rich approaches to summarization covers such things as Wendy Lehnert's work on breaking