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|a UAMI
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| 245 |
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|a Advances in automatic text summarization /
|c edited by Inderjeet Mani and Mark T. Maybury.
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| 260 |
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|a Cambridge, Mass. :
|b MIT Press,
|c ©1999.
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| 300 |
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|a 1 online resource (xv, 434 pages) :
|b illustrations
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a data file
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| 504 |
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|a Includes bibliographical references and index.
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|a Preface -- Introduction ; 1. Automatic summarizing: Factors and directions -- Section 1: The classical approaches ; 2. The automatic creation of literature abstracts ; 3. New methods in automatic extracting ; 4. Automatic abstracting research at chemical abstracts service -- Section 2: Corpus-based approaches ; 5. A trainable document summarizer ; 6. Development and evaluation of a statistically based document summarization system ; 7. A trainable summarizer with knowledge acquired from robust NLP techniques ; 8. Automated text summarization in SUMMARIST E. -- Section 3: Exploiting discourse structure ; 9. Salience-based content characterization of text documents ; 10. Using lexical chains for text summarization ; 11. Discourse, trees are good indicators of importance in text ; 12. A robust practical text summarizer ; 13. Argumentative classification of extracted sentences as a first step towards flexible abstracting -- Section 4: Knowledge-rich approaches ; 14. Plot units: A narrative summarization strategy ; 15. Knowledge-based text summarization: Salience and generalization operators for knowledge base abstraction ; 16. Generating concise natural language summaries ; 17. Generating summaries from event data -- Section 5: Evaluation methods ; 18. The formation of abstracts by the selection of sentences ; 19. Automatic condensation of electronic publications by sentence selection ; 20. The effects and limitations of automated text condensing on reading comprehension performance ; 21. An evaluation of automatic text summarization systems -- Section 6: New summarization problem areas ; 22. Automatic text structuring and summarization ; 23. Summarizing similarities and differences among related documents ; 24. Generating summaries of multiple news articles ; 25. An empirical study of the optimal presentation of multimedia summaries of broadcast news ; 26. Summarization of diagrams in documents -- Index.
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|a Print version record.
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| 546 |
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|a English.
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| 590 |
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|a eBooks on EBSCOhost
|b EBSCO eBook Subscription Academic Collection - Worldwide
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| 650 |
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0 |
|a Automatic abstracting.
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| 650 |
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0 |
|a Computational linguistics.
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| 650 |
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6 |
|a Résumés automatiques.
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| 650 |
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6 |
|a Linguistique informatique.
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| 650 |
|
7 |
|a computational linguistics.
|2 aat
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| 650 |
|
7 |
|a LANGUAGE ARTS & DISCIPLINES
|x Library & Information Science
|x General.
|2 bisacsh
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| 650 |
|
7 |
|a Automatic abstracting
|2 fast
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| 650 |
|
7 |
|a Computational linguistics
|2 fast
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| 650 |
1 |
7 |
|a Automatisering.
|2 gtt
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| 650 |
1 |
7 |
|a Abstracting.
|2 gtt
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| 650 |
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7 |
|a Languages & Literatures.
|2 hilcc
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| 650 |
|
7 |
|a Philology & Linguistics.
|2 hilcc
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| 700 |
1 |
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|a Mani, Inderjeet.
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| 700 |
1 |
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|a Maybury, Mark T.
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| 776 |
0 |
8 |
|i Print version:
|t Advances in automatic text summarization.
|d Cambridge, Mass. : MIT Press, ©1999
|z 0262133598
|w (DLC) 99022688
|w (OCoLC)41070720
|
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