C4.5: programs for machine learning
C4.5: programs for machine learning
A maximum entropy approach to natural language processing
Computational Linguistics
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Self-organizing Markov models and their application to part-of-speech tagging
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Equations for part-of-speech tagging
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
ME-based biomedical named entity recognition using lexical knowledge
ACM Transactions on Asian Language Information Processing (TALIP)
Semantic Classification of Bio-Entities Incorporating Predicate-Argument Features
IEICE - Transactions on Information and Systems
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The snapshot of a word means the most informative fragment of the word. By taking the snapshot instead of the whole, the value space of lexical features can be significantly reduced. From the perspective of machine learning, a small space of feature values implies a loss of information but less data-spareness and less unseen data. The snapshot of words can be taken by using the word folding technique, the goal of which is to reduce the value space of lexical features while minimizing the loss of information.