Automatically extracting highlights for TV Baseball programs
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Statistics-Based Summarization - Step One: Sentence Compression
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Discourse Segmentation in Aid of Document Summarization
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 3 - Volume 3
Automatic Summarization of Web Content to Smaller Display Devices
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Web Page Summarization for Handheld Devices: A Natural Language Approach
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
A simple rule-based part of speech tagger
ANLC '92 Proceedings of the third conference on Applied natural language processing
Information fusion in the context of multi-document summarization
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Query-relevant summarization using FAQs
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Learning-based summarisation of XML documents
Information Retrieval
The use of summaries in XML retrieval
ECDL'06 Proceedings of the 10th European conference on Research and Advanced Technology for Digital Libraries
Automatic text summarization based on lexical chains
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Combining summaries using unsupervised rank aggregation
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part II
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The process of summarizing documents is becomingincreasingly important in the light of recent advances indocument creation/distribution technology, and theresulting influx of large numbers of documents in everyday life. This paper presents a document summarizer thatcombines document analysis, structural decomposition,XML representation and lexical chain analysis. Theproposed summarizer is compared to three commerciallyavailable summarizers and it is shown that it produceseither comparable or better summaries overall.