The Leading eBooks Store Online

for Kindle Fire, Apple, Android, Nook, Kobo, PC, Mac, Sony Reader ...

New to eBooks.com?

Learn more

Named Entities

Recognition, classification and use

Named Entities
Add to cart
US$ 120.00
(If any tax is payable it will be calculated and shown at checkout.)
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).
John Benjamins Publishing Company; July 2009
176 pages; ISBN 9789027289223
Read online, or download in secure PDF format