[PDF] Top 20 Dependency based Gated Recursive Neural Network for Chinese Word Segmentation
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Dependency based Gated Recursive Neural Network for Chinese Word Segmentation
... We also compare DGRNN with other state-of- the-art non-neural networks, as shown in Table 2. Chen et al. (2015) implements the work of Sun and Xu (2011) on CTB6 dataset and achieves 95.7% F-score. We achieve the ... See full document
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Long Short Term Memory Neural Networks for Chinese Word Segmentation
... a neural model based on Long Short-Term Memory Neural Network (LSTM) (Hochreiter and Schmid- huber, 1997) that explicitly model the previous information by exploiting input, output and for- ... See full document
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Max Margin Tensor Neural Network for Chinese Word Segmentation
... Tensor-based transformation was also used in other neural network models for its ability to cap- ture multiple interactions in data. For example, Socher et al. (2013b) exploited tensor-based ... See full document
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A Dependency Based Neural Network for Relation Classification
... As shown in Table 2, DepNN achieves the best result (83.6) using NER features. WordNet fea- tures can also improve the performance of DepN- N, but not as obvious as NER. Yu et al. (2014) had similar observations, since ... See full document
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Neural Word Segmentation Learning for Chinese
... to Chinese word segmentation formalize this prob- lem as a character-based sequence label- ing task so that only contextual informa- tion within fixed sized local windows and simple ... See full document
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Enhancing the Inside Outside Recursive Neural Network Reranker for Dependency Parsing
... n = 200 in the Le and Zuidema’s reranker). Constructing a binary tree for this hierarchi- cal softmax turns out to be nontrivial. Morin and Bengio (2005) relied on WordNet whereas Mikolov et al. (2013) used only ... See full document
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A Re ranking Model for Dependency Parser with Recursive Convolutional Neural Network
... a dependency tree with the dense representations. We propose a recursive convolutional neural network (RCNN) architecture to capture syntac- tic and compositional-semantic represen- tations of ... See full document
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Fast and Accurate Neural Word Segmentation for Chinese
... engineering, neural word segmentation has been actively stud- ied ...sliding-window based sequence labeling (Col- lobert et ...a gated recursive neural network ... See full document
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The Inside Outside Recursive Neural Network model for Dependency Parsing
... appropriate word vectors (Baroni et ...and dependency parses ...alternative based on recursive neural ...existing neural network architecture can be used in this ...rent ... See full document
11
Transition Based Neural Word Segmentation
... ral network to achieve extensive feature combi- nations, capturing the interaction between charac- ters and ...sive network structure to the same end, extract- ing more combined features to model ... See full document
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Segment Level Sequence Modeling using Gated Recursive Semi Markov Conditional Random Fields
... proposing Gated Recursive Semi-Markov Condi- tional Random Fields (grSemi-CRFs), which can automatically learn features for segment-level se- quence tagging ...a neural-based feature extrac- ... See full document
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Chain Based RNN for Relation Classification
... a recursive neural network (RNN), based on the shortest path between two entities in a dependency ...are based on constituency- based parsing because phrasal nodes in a ... See full document
6
Transition based Dependency Parsing Using Two Heterogeneous Gated Recursive Neural Networks
... structured recursive neural network with gate mechanism to model the combination of features extracted from stack and ...the gated version ... See full document
11
Convolutional Neural Network with Word Embeddings for Chinese Word Segmentation
... tag Chinese characters into one of four position tags, and then coverted these tags into a segmentation using ...various neural models have been explored for ...feed-forward neural ... See full document
10
Gated Recursive Neural Network for Chinese Word Segmentation
... We use three popular datasets, PKU, MSRA and CTB6, to evaluate our model on newswire texts. The PKU and MSRA data are provided by the second International Chinese Word Segmentation Bakeoff (Emerson, ... See full document
10
Sentence Modeling with Gated Recursive Neural Network
... Recently, neural network based sentence modeling methods have achieved great ...cursive neural networks (RecNNs) can ef- fectively model the combination of the words in ...a gated ... See full document
6
Neural Regularized Domain Adaptation for Chinese Word Segmentation
... where ⊗ is convolution operator, m and b are the weight matrix of filter and bias, f is the non-linear function such as ReLU in our network. And for each window size, multiple filters are applied to generate ... See full document
10
Chinese Segmentation with a Word Based Perceptron Algorithm
... Several discriminatively trained models have re- cently been applied to the CWS problem. Exam- ples include Xue (2003), Peng et al. (2004) and Shi and Wang (2007); these use maximum entropy ( ME ) and conditional random ... See full document
8
Analyzing and inferring human real-life behavior through online social networks with social influence deep learning
... monolithic concept, but it reflects several distinct ideas. For this reason, to be meaningful, any assertion regarding interpretability should fix a specific definition. Lipton describes two categories of ... See full document
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