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(Ebook) Named Entities : Recognition, classification and use by Satoshi Sekine; Elisabete Ranchhod ISBN 9789027289223, 9027289220

  • SKU: EBN-51680050
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Authors:Satoshi Sekine; Elisabete Ranchhod
Pages:176 pages.
Year:2009
Editon:1
Publisher:John Benjamins Publishing Company
Language:english
File Size:2.08 MB
Format:pdf
ISBNS:9789027289223, 9027289220
Categories: Ebooks

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(Ebook) Named Entities : Recognition, classification and use by Satoshi Sekine; Elisabete Ranchhod ISBN 9789027289223, 9027289220

Named Entities provides critical information for many NLP applications. Named Entity recognition and classification (NERC) in text is recognized as one of the important sub-tasks of Information Extraction (IE). The seven papers in this volume cover various interesting and informative aspects of NERC research. Nadeau & Sekine provide an extensive survey of past NERC technologies, which should be a very useful resource for new researchers in this field. Smith & Osborne describe a machine learning model which tries to solve the over-fitting problem. Mazur & Dale tackle a common problem of NE and conjunction; as conjunctions are often a part of NEs or appear close to NEs, this is an important practical problem. A further three papers describe analyses and implementations of NERC for different languages: Spanish (Galicia-Haro & Gelbukh), Bengali (Ekbal, Naskar & Bandyopadhyay), and Serbian (Vitas, Krstev & Maurel). Finally, Steinberger & Pouliquen report on a real WEB application where multilingual NERC technology is used to identify occurrences of people, locations and organizations in newspapers in different languages. The contributions to this volume were previously published in Lingvisticae Investigationes 30:1 (2007).
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