000 | 05259nam a22005655i 4500 | ||
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001 | 978-3-642-28569-1 | ||
003 | DE-He213 | ||
005 | 20140220082846.0 | ||
007 | cr nn 008mamaa | ||
008 | 120814s2013 gw | s |||| 0|eng d | ||
020 |
_a9783642285691 _9978-3-642-28569-1 |
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024 | 7 |
_a10.1007/978-3-642-28569-1 _2doi |
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050 | 4 | _aQA76.9.D343 | |
072 | 7 |
_aUNF _2bicssc |
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_aUYQE _2bicssc |
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_aCOM021030 _2bisacsh |
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082 | 0 | 4 |
_a006.312 _223 |
100 | 1 |
_aPoibeau, Thierry. _eeditor. |
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245 | 1 | 0 |
_aMulti-source, Multilingual Information Extraction and Summarization _h[electronic resource] / _cedited by Thierry Poibeau, Horacio Saggion, Jakub Piskorski, Roman Yangarber. |
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2013. |
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300 |
_aXX, 323 p. 55 illus., 21 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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490 | 1 |
_aTheory and Applications of Natural Language Processing, _x2192-032X |
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505 | 0 | _aPart I Background and Fundamentals -- 1.Automatic Text Summarization: Past, Present and Future. Horacio Saggion and Thierry Poibeau -- Information Extraction: Past, Present and Future. Jakub Piskorski and Roman Yangarber -- Part II Named Entity in a Multilingual Context -- Learning to Match Names Across Languages. Inderjeet Mani, Alex Yeh, and Sherri Condon -- Computational Methods for Name Normalization Using Hypocoristic Personal Name Variants. Patricia Driscoll -- Entity Linking: Finding Extracted Entities in a Knowledge Base. Delip Rao, Paul McNamee, and Mark Dredze -- A Study of the Effect of Document Representations in Clustering-based Cross-document Coreference Resolution. Horacio Saggion -- Part III Information Extraction -- Interactive Topic Graph Extraction and Exploration of Web Content. Günter Neumann and Sven Schmeier -- Predicting Relevance of Event Extraction for the End User. Silja Huttunen, Arto Vihavainen, Mian Du, and Roman Yangarber -- Open-domain Multi-Document Summarization via Information Extraction: Challenges and Prospects. Heng Ji, Benoit Favre, Wen-Pin Lin, Dan Gillick, Dilek Hakkani-Tur, and Ralph Grishman -- Part IV Multi-document Summarization -- Generating Update Summaries: Using an Unsupervized Clustering Algorithm to Cluster Sentences. Aurélien Bossard -- Multilingual Statistical News Summarization. Mijail Kabadjov, Josef Steinberger and Ralf Steinberger -- A Bottom-up Approach to Sentence Ordering for Multi-document Summarization. Danushka Bollegala, Naoaki Okazaki, and Mitsuru Ishizuka -- Improving Speech-to-Text Summarization by Using Additional Information Sources. Ricardo Ribeiro and David Martins de Matos -- Multi-Document Summarization Techniques for Generating Image Descriptions: A Comparative Analysis. Ahmet Aker, Laura Plaza, Elena Lloret, and Robert Gaizauskas -- Index. | |
520 | _aInformation extraction (IE) and text summarization (TS) are powerful technologies for finding relevant pieces of information in text and presenting them to the user in condensed form. The ongoing information explosion makes IE and TS critical for successful functioning within the information society. These technologies face particular challenges due to the inherent multi-source nature of the information explosion. The technologies must now handle not isolated texts or individual narratives, but rather large-scale repositories and streams---in general, in multiple languages---containing a multiplicity of perspectives, opinions, or commentaries on particular topics, entities or events. There is thus a need to adapt existing techniques and develop new ones to deal with these challenges. This volume contains a selection of papers that present a variety of methodologies for content identification and extraction, as well as for content fusion and regeneration. The chapters cover various aspects of the challenges, depending on the nature of the information sought---names vs. events,--- and the nature of the sources---news streams vs. image captions vs. scientific research papers, etc. This volume aims to offer a broad and representative sample of studies from this very active research field. | ||
650 | 0 | _aComputer science. | |
650 | 0 | _aData mining. | |
650 | 0 | _aInformation storage and retrieval systems. | |
650 | 0 | _aComputational linguistics. | |
650 | 0 | _aSemantics. | |
650 | 1 | 4 | _aComputer Science. |
650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
650 | 2 | 4 | _aComputational Linguistics. |
650 | 2 | 4 | _aInformation Storage and Retrieval. |
650 | 2 | 4 | _aInformation Systems Applications (incl. Internet). |
650 | 2 | 4 | _aSemantics. |
700 | 1 |
_aSaggion, Horacio. _eeditor. |
|
700 | 1 |
_aPiskorski, Jakub. _eeditor. |
|
700 | 1 |
_aYangarber, Roman. _eeditor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783642285684 |
830 | 0 |
_aTheory and Applications of Natural Language Processing, _x2192-032X |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-642-28569-1 |
912 | _aZDB-2-SHU | ||
999 |
_c96862 _d96862 |