Improving Summaries by Revising Them

Improving Summaries by Revising Them Inderjeet Mani and Barbara Gates and Eric Bloedorn The MITRE Corporation 11493 Sunset Hills Rd. Reston, VA 22090, USA {imani,blgates,bloedorn}@mitre.org Abstract This paper describes a program which revises a draft text by aggregating together descriptions of discourse entities, in addition to deleting ex- traneous information. In contrast to knowledge- rich sentence aggregation approaches explored in the past, this approach exploits statistical parsing and robust coreference detection. In an evaluation involving revision of topic-related summaries using informativeness measures from the TIPSTER SUMMAC evaluation, the results show gains in informativeness without compro- mising readability. 1 Introduction Writing improves with revision. Authors are fa- miliar with the process of condensing a long pa- per into a shorter one: this is an iterative pro- cess, with the results improved over successive drafts. Professional abstractors carry out sub- stantial revision and editing of abstracts (Crem- rains 1996). We therefore expect revision to be useful in automatic text summarization. Prior research exploring the use of revision in sum- marization, e.g., (Gabriel 1988), (Robin 1994), (McKeown et al. 1995) has focused mainly on structured data as the input. Here, we exam- ine the use of revision in summarization of text input. First, we review some summarization termi- nology. In revising draft summaries, these con- densation operations, as well as stylistic reword- ing of sentences, play an important role. Sum- maries can be used to indicate what topics are addressed in the source text, and thus can be used to alert the user as to the source con- tent (the indicative function). Summaries can also be used to cover the concepts in the source text to the extent possible given the compres- sion requirements for the summary (the in for- mative function). Summaries can be tailored to a reader's interests and expertise, yielding topic- related summaries, or they can be aimed at a particular- usually broad - readership commu- nity, as in the cash of (so-called) generic sum- maries. Revision here applies to generic and topic-related informative summaries, intended for publishing and dissemination. Summarization can be viewed as a text-to- text reduction operation involving three main condensation operations: selection of salient portions of the text, aggregation of information from different portions of the text, and abstrac- tion of specific information with more general information (Mani and Maybury 1999). Our approach to revision is to construct an initial draft summary of a source text and then to add to the draft additional background information. Rather than concatenate material in the draft (as surface-oriented, sentence extraction sum- marizers do), information in the draft is com- bined and excised based on revision rules in- volving aggregation (Dalianis and Hovy 1996) and elimination operations. Elimination can increase the amount of compression (summary length/source length) available, while aggrega- tion can potentially gather and draw in relevant background information, in the form of descrip- tions of discourse entities from different parts of the source. We therefore hypothesize that these operations can result in packing in more infor- mation per …

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