Character-based feature extraction with LSTM networks for POS-tagging task
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17 citations
17 citations
Cites background from "Character-based feature extraction ..."
...It is becoming increasingly popular to use richer architectures to learn better embeddings from characters/words (Yessenbayev and Makazhanov, 2016; Ling et al., 2015; Wieting et al., 2016)....
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14 citations
Cites background from "Character-based feature extraction ..."
...Zhandos Yessenbayev [11] discussed a character-based feature extraction with LSTM networks for POS-tagging task....
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...Great success in several studies [5] [6][11][13][14][15] of sequence labeling task by using three recurrent neural networks is the motivation of this work....
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5 citations
4 citations
References
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"Character-based feature extraction ..." refers background in this paper
...The long short-term memory (LSTM) architecture was proposed by Hochreiter and Schmidhuber [9] and it consists of four major components a self-connected memory cell and three multiplicative units – the input, output and forget gates [7]....
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"Character-based feature extraction ..." refers methods in this paper
...Possible alternatives are global vectors for representations [27], which capture both the statistical information via count-based methods and meaningful structures via the log-bilinear prediction-based methods....
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20,077 citations