Wentworth
Institute of Technology
Named entities : recognition, classification, and use /
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...
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| Other Authors: | , |
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| Format: | Electronic eBook |
| Language: | English |
| Published: |
Amsterdam ; Philadelphia :
John Benjamins Pub. Co.,
©2009.
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| Series: | Benjamins current topics ;
v. 19. |
| Subjects: | |
| Online Access: |
Full text (Wentworth users only) |
| Local Note: | ProQuest Ebook Central |
| Summary: | 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. |
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| Item Description: | Previously published in Lingvisticae investigationes 30:1 (2007). |
| Physical Description: | 1 online resource (168 pages) : illustrations |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9789027289223 9027289220 9027222495 9789027222497 1282245317 9781282245310 9786612245312 661224531X |
| ISSN: | 1874-0081 ; |
| Language: | English. |
| Source of Description, Etc. Note: | Print version record. |