The identification of important concepts in highly structured technical papers
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
The decomposition of human-written summary sentences
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Generating natural language summaries from multiple on-line sources
Computational Linguistics - Special issue on natural language generation
Temporal summaries of new topics
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Generating indicative-informative summaries with sumUM
Computational Linguistics - Summarization
Proceedings of the 21st annual international conference on Documentation
SUMMAC: a text summarization evaluation
Natural Language Engineering
Meta-evaluation of summaries in a cross-lingual environment using content-based metrics
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Producing biographical summaries: combining linguistic knowledge with corpus statistics
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Using a text engineering framework to build an extendable and portable IE-based summarisation system
AS '02 Proceedings of the ACL-02 Workshop on Automatic Summarization - Volume 4
Automatic summarising: The state of the art
Information Processing and Management: an International Journal
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We describe a method of text summarization that produces indicative-informative abstracts for technical papers. The abstracts are generated by a process of conceptual identification, topic extraction and re-generation. We have carried out an evaluation to assess indicativeness and text acceptability relying on human judgment. The results so far indicate good performance in both tasks when compared with other summarization technologies.