Algorithms for Minimum Risk Chunking

Stochastic finite automata are useful for identifying substrings (chunks) within larger units of text. Relevant applications include tokenization, base-NP chunking, named entity recognition, and other information extraction tasks. For a given input string, a stochastic automaton represents a probabi...

Ausführliche Beschreibung

Bibliographische Detailangaben

1. Verfasser:	Jansche, Martin
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Applied sciences Artificial intelligence Computer science control theory systems Empirical Risk Minimization Entity Recognition Exact sciences and technology Label Sequence Natural Language Processing Noun Phrase Speech and sound recognition and synthesis. Linguistics
Online-Zugang:	Volltext
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