Sequence labeling

In machine learning, sequence labeling is a type of pattern recognition task that involves the algorithmic assignment of a categorical label to each… (More)
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Papers overview

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Highly Cited
2017
Highly Cited
2017
Fischler PER •Sequence of tokens mapped to word embeddings. •Bidirectional LSTM builds context-dependent representations for each… (More)
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Highly Cited
2016
Highly Cited
2016
State-of-the-art sequence labeling systems traditionally require large amounts of taskspecific knowledge in the form of… (More)
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Highly Cited
2015
Highly Cited
2015
OBJECTIVE Social media is becoming increasingly popular as a platform for sharing personal health-related information. This… (More)
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2013
2013
The increasingly popular use of Crowdsourcing as a resource to obtain labeled data has been contributing to the wide awareness of… (More)
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2010
2010
The Viterbi algorithm is the conventional decoding algorithm most widely adopted for sequence labeling. Viterbi decoding is… (More)
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Highly Cited
2009
Highly Cited
2009
Supervised sequence-labeling systems in natural language processing often suffer from data sparsity because they use word types… (More)
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2009
2009
While Active Learning (AL) has already been shown to markedly reduce the annotation efforts for many sequence labeling tasks… (More)
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Review
2008
Review
2008
Active learning is well-suited to many problems in natural language processing, where unlabeled data may be abundant but… (More)
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Highly Cited
2005
Highly Cited
2005
This paper presents a bidirectional inference algorithm for sequence labeling problems such as part-of-speech tagging, named… (More)
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Highly Cited
1983
Highly Cited
1983
A large class of problems can be formulated in terms of the assignment of labels to objects. Frequently, processes are needed… (More)
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