[PDF] Top 20 Feature based Neural Language Model and Chinese Word Segmentation
Has 10000 "Feature based Neural Language Model and Chinese Word Segmentation" found on our website. Below are the top 20 most common "Feature based Neural Language Model and Chinese Word Segmentation".
Feature based Neural Language Model and Chinese Word Segmentation
... on segmentation used much more sophisticated feature templates other than the one introduced ...of-the-art segmentation work is not the main pur- pose of this ...our model can use the same ... See full document
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Word Segmentation on Chinese Mirco Blog Data with a Linear Time Incremental Model
... the model we designed for the word segmentation bake-off on Chinese micro-blog data in the 2nd CIPS-SIGHAN joint conference on Chinese language ...incremental word segmen- ... See full document
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Dependency based Gated Recursive Neural Network for Chinese Word Segmentation
... However, these models focus more on collect- ing local features while long distance dependen- cies are not well learned. In fact, relying on the information of adjacent words is not enough for CWS task. An example is ... See full document
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Fast and Accurate Neural Word Segmentation for Chinese
... non- neural-network components for performance en- hancement, their performance drops rapidly when solely depending on neural ...combination neural network over characters for word ... See full document
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An Double Hidden HMM and an CRF for Segmentation Tasks with Pinyin’s Finals
... our Chinese word segmentation based on the proposed conditional support vector Markov models for sequential labeling tasks, especially Chinese word segmen- ...SIGHAN-3 ... See full document
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Chinese Named Entity Recognition and Word Segmentation Based on Character
... of feature templates (only differ in window size, or punctuations) are used to train several different models, and finally achieve a group of ...same Chinese character string in result A and ... See full document
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A Character Based Joint Model for Chinese Word Segmentation
... tive model or adopting a discriminative model. The generative model learns the joint probabil- ity of the given input and its associated label sequence, while the discriminative model learns ... See full document
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Is Word Segmentation Necessary for Deep Learning of Chinese Representations?
... Firstly, word data sparsity inevitably leads to overfitting and the ubiquity of OOV words limits the model’s learning ...including Chinese. Frequencies of many Chinese words are extremely small, ... See full document
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Transition Based Neural Word Segmentation
... extensive feature combi- nations, capturing the interaction between charac- ters and ...to model complicated character combinations in a five-character win- ...LSTM model to capture long-range ... See full document
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A Realistic and Robust Model for Chinese Word Segmentation
... a word in a language. [12] work based on mutual information (MI) is the best-known and most comprehensive in this ...of language and yet be highly ... See full document
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A Joint Model for Unsupervised Chinese Word Segmentation
... joint model for un- supervised Chinese word ...joint model is a combination of the HDP-based model, which is a word-based model, and HMM-based ... See full document
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Morphological Analysis for Unsegmented Languages using Recurrent Neural Network Language Model
... grated language models into morphological anal- ...improved Chinese word segmentation and POS tagging by using N-gram features learned from an automatically segmented ...contains ... See full document
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Which Performs Better on In Vocabulary Word Segmentation: Based on Word or Character?
... character- based tagging outperforms dictionary-based seg- mentation not only on OOV words but also on IV words within Bakeoff closed ...IV word and overall ...statistic language model ... See full document
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Discriminative Pruning of Language Models for Chinese Word Segmentation
... base model is used as the criterion for model ...method based on Kullback-Leibler distance as the ...any model size. Correlation between language model perplexity and system ... See full document
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Neural Regularized Domain Adaptation for Chinese Word Segmentation
... the feature distribution from adapted model to be close to that from the unadapted model (Yu et ...the feature distributions over the differ- ent domains are close to each ...a neural ... See full document
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Unsupervised Neural Word Segmentation for Chinese via Segmental Language Modeling
... bigram language model based on HDP (Teh et ...archical language model using Pitman-Yor (PY) process, which can generate sentences hierarchi- ...HMM model for unsupervised CWS ... See full document
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Convolutional Neural Network with Word Embeddings for Chinese Word Segmentation
... Many neural network models have been explored for ...n-gram feature must be used ...volutional neural networks (CNNs) have shown its great effectiveness in computer vision tasks (Krizhevsky et ... See full document
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Gated Recursive Neural Network for Chinese Word Segmentation
... sufficiently model the complicated combination features for its simplicity in ...recurrent neural network (Cho et ...recursive neural net- work (GRNN) by introducing two kinds of gates, namely “reset ... See full document
10
Neural Word Segmentation Learning for Chinese
... Recently, neural models have been widely used for NLP tasks for their ability to minimize the ef- fort in feature ...general neural network architecture for sequence labeling pro- posed in (Collobert ... See full document
12
Improving Named Entity Recognition for Chinese Social Media with Word Segmentation Representation Learning
... where word boundaries are not readily identified in text, word segmentation is a key first step to generating features for an NER ...using word boundary tags as features are helpful, the ... See full document
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