Information extraction as a basis for portable text classification systems
Information extraction as a basis for portable text classification systems
Named Entity Extraction using AdaBoost
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Named entity recognition as a house of cards: classifier stacking
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Introduction to the CoNLL-2002 shared task: language-independent named entity recognition
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Boosting for named entity recognition
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Named entity recognition with character-level models
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
A context pattern induction method for named entity extraction
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Self-training and co-training applied to spanish named entity recognition
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
Automatic rule learning exploiting morphological features for named entity recognition in Turkish
Journal of Information Science
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Named entity recognition (NER) is a subtask of information extraction (IE) which can be used further on for different purposes. In this paper, we discuss named entity recognition for Ukrainian language, which is a Slavonic language with a rich morphology. The approach we follow uses a restricted number of features. We show that it is feasible to boost performance by considering several heuristics and patterns acquired from the Web data.