Revision-based generation of natural language summaries providing historical background: corpus-based analysis, design, implementation and evaluation
Aggregation in Natural Language Generation
EWNLG '93 Selected papers from the Fourth European Workshop on Trends in Natural Language Generation, An Artificial Intelligence Perspective
Practical issues in automatic documentation generation
ANLC '94 Proceedings of the fourth conference on Applied natural language processing
Summarizing text documents: sentence selection and evaluation metrics
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Creating and evaluating multi-document sentence extract summaries
Proceedings of the ninth international conference on Information and knowledge management
Describing complex charts in natural language: a caption generation system
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Generating natural language summaries from multiple on-line sources
Computational Linguistics - Special issue on natural language generation
Language generation for multimedia healthcare briefings
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Segregatory coordination and ellipsis in text generation
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Multi-document summarization by sentence extraction
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLPWorkshop on Automatic summarization - Volume 4
Choosing the content of textual summaries of large time-series data sets
Natural Language Engineering
Natural language directed inference from ontologies
Artificial Intelligence
Multi-document summarization by sentence extraction
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLP Workshop on Automatic Summarization
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Aggregating different pieces of similar information is necessary to generate concise and easy to understand reports in technical domains. This paper presents a general algorithm that combines similar messages in order to generate one or more coherent sentences for them. The process is not as trivial as might be expected. Problems encountered are briefly described.