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CICLING
2007
Springer
15 years 3 months ago
Handling Conjunctions in Named Entities
Although the literature contains reports of very high accuracy figures for the recognition of named entities in text, there are still some named entity phenomena that remain probl...
Robert Dale, Pawel P. Mazur
ECCC
2008
117views more  ECCC 2008»
14 years 9 months ago
The complexity of learning SUBSEQ(A)
Higman essentially showed that if A is any language then SUBSEQ(A) is regular, where SUBSEQ(A) is the language of all subsequences of strings in A. Let s1, s2, s3, . . . be the sta...
Stephen A. Fenner, William I. Gasarch, Brian Posto...
TNN
1998
92views more  TNN 1998»
14 years 9 months ago
Inductive inference from noisy examples using the hybrid finite state filter
—Recurrent neural networks processing symbolic strings can be regarded as adaptive neural parsers. Given a set of positive and negative examples, picked up from a given language,...
Marco Gori, Marco Maggini, Enrico Martinelli, Giov...
EMNLP
2009
14 years 7 months ago
Real-Word Spelling Correction using Google Web 1T 3-grams
We present a method for detecting and correcting multiple real-word spelling errors using the Google Web 1T 3-gram data set and a normalized and modified version of the Longest Co...
Aminul Islam, Diana Inkpen
ACL
2012
13 years 3 days ago
Machine Translation without Words through Substring Alignment
In this paper, we demonstrate that accurate machine translation is possible without the concept of “words,” treating MT as a problem of transformation between character string...
Graham Neubig, Taro Watanabe, Shinsuke Mori, Tatsu...