TY - JOUR
AU - 
AB - We are IntechOpen, the world’s leading publisher of Open Access books Built by scientists, for scientists 135,000 165M 5,500 Open access books available International authors and editors Downloads Our authors are among the TOP 1% 12.2% Countries delivered to Contributors from top 500 universities most cited scientists Selection of our books indexed in the Book Citation Index in Web of Science™ Core Collection (BKCI) Interested in publishing with us? Contact book.department@intechopen.com Numbers displayed above are based on latest data collected. For more information visit www.intechopen.com Chapter 8 Biomedical Named Entity Recognition: A Survey of Machine-Learning Tools David Campos, Sérgio Matos and José Luís Oliveira Additional information is available at the end of the chapter http://dx.doi.org/10.5772/51066 1. Introduction It is well known that the rapid growth and dissemination of the Internet has resulted in huge amounts of information generated and shared, available in the form of textual data, images, videos or sounds. This overwhelming surge of data is also true for specific areas such as biomedicine, where the number of published documents, such as articles, books and technical reports, is increasing exponentially. For instance, the MEDLINE literature database contains over 20 million references to journal papers, covering a wide range 
TI - Theory and Applications for Advanced Text Mining: Biomedical Named Entity Recognition: A Survey of Machine-Learning Tools
JF - Theory and Applications for Advanced Text Mining
DO - 10.5772/51066
DA - 2012-11-21
UR - https://www.deepdyve.com/lp/unpaywall/theory-and-applications-for-advanced-text-mining-biomedical-named-P1d1gpCLo6
DP - DeepDyve
ER -