Constructing literature abstracts by computer: techniques and prospects
Information Processing and Management: an International Journal - Special issue on natural language processing and information retrieval
A trainable document summarizer
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Generating summaries of multiple news articles
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Automatic condensation of electronic publications by sentence selection
Information Processing and Management: an International Journal - Special issue: summarizing text
TextTiling: segmenting text into multi-paragraph subtopic passages
Computational Linguistics
The rhetorical parsing of natural language texts
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Abstract generation based on rhetorical structure extraction
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
A self-learning universal concept spotter
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Extracting key paragraph based on topic and event detection: towards multi-document summarization
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLPWorkshop on Automatic summarization - Volume 4
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We present an automated method of generating human-readable summaries from a variety of text documents including newspaper articles, business reports, government documents, even broadcast news transcripts. Our approach exploits an empirical observation that much of the written text display certain regularities of organization and style, which we call the Discourse Macro Structure (DMS). A summary is therefore created to reflect the components of a given DMS. In order to produce a coherent and readable summary we select continuous, well-formed passages from the source document and assemble them into a mini-document within a DMS template. In this paper we describe an automated summarizer that can generate both short indicative abstracts, useful for quick scanning of a list of documents, as well as longer informative digests that can serve as surrogates for the full text. The summarizer can assist the users of an information retrieval system in assessing the quality of the results returned from a search, preparing reports and memos for their customers, and even building more effective search queries.