TY - GEN
T1 - A systematic comparison of feature-rich probabilistic classifiers for NER tasks
AU - Rosenfeld, Benjamin
AU - Fresko, Moshe
AU - Feldman, Ronen
PY - 2005
Y1 - 2005
N2 - In the CoNLL 2003 NER shared task, more than two thirds of the submitted systems used the feature-rich representation of the task. Most of them used maximum entropy to combine the features together. Others used linear classifiers, such as SVM and RRM. Among all systems presented there, one of the MEMM-based classifiers took the second place, losing only to a committee of four different classifiers, one of which was ME-based and another RRM-based. The lone RRM was fourth, and CRF came in the middle of the pack. In this paper we shall demonstrate, by running the three algorithms upon the same tasks under exactly the same conditions that this ranking is due to feature selection and other causes and not due to the inherent qualities of the algorithms, which should be ranked otherwise.
AB - In the CoNLL 2003 NER shared task, more than two thirds of the submitted systems used the feature-rich representation of the task. Most of them used maximum entropy to combine the features together. Others used linear classifiers, such as SVM and RRM. Among all systems presented there, one of the MEMM-based classifiers took the second place, losing only to a committee of four different classifiers, one of which was ME-based and another RRM-based. The lone RRM was fourth, and CRF came in the middle of the pack. In this paper we shall demonstrate, by running the three algorithms upon the same tasks under exactly the same conditions that this ranking is due to feature selection and other causes and not due to the inherent qualities of the algorithms, which should be ranked otherwise.
UR - http://www.scopus.com/inward/record.url?scp=33646395384&partnerID=8YFLogxK
U2 - 10.1007/11564126_24
DO - 10.1007/11564126_24
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AN - SCOPUS:33646395384
SN - 3540292446
SN - 9783540292449
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 217
EP - 227
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2005
Y2 - 3 October 2005 through 7 October 2005
ER -