Then the attribute words in the test QA pairs can be used to calculate the matching scores . The experimental results show that the proposed representation method of QA patterns has good flexibility to deal with the uncertainty caused by the Chinese word segmentation , and the proposed method has good performance at both MAP and MRR on the test data . In the text mining , the technology of Chinese automatic word segmentation is a difficult problem that the computer science has to face . Aiming at the characteristics of Chinese writing , such as no space between words , continuous writing in sentences and difficulty of segmenting the ambiguous words , the grammatical phenomena are summarized which lie in the typical ambiguity , and the codes library of different parts of speech used for coding is built up . As one of the important problem in the field of Chinese automatic word segmentation and Chinese information process , part of speech tagging is the research difficulty and emphases in the filed . The precision of POS tagging to syntactic category has influenced badly the quality of POS tagging . Identifying Textual Entailment is the task of finding the relationship between the given hypothesis and text fragments . Developing a high-performance text paraphrasing system usually requires rich external knowledge such as syntactic parsing , thesaurus which is limited in Chinese since the Chinese word segmentation problem should be resolve first . By following last year , in this year , we continue adopting the created RITE system and combine with multiple online available thesaurus . For the Chinese word segmentation problem the BP algorithm has relatively slow convergence speed . Here the Levenbery-Marquart algorithm is introduced to optimize the Chinese word segmentation system based on the neural network . According to the features of Chinese documents , this paper designs and implements the Chinese Text Clustering System to perform automatic clustering of Chinese documents . Firstly , this system will carry out Chinese word automatic segmentation for the input Chinese document sets by using reverse maximum matching method . Secondly , further text preprocessing is performed . In order to identify new words in huge Chinese corpus efficiently , this paper comes up with an algorithm based on ensemble methods . At first we perform Chinese word segmenting with Trie and build segment-tree . Then we select words pattern drawing method , frequency filtering , independent word probability and naive Bayes model to be sub-models of ensemble methods and train them independently . The invention discloses an intelligent statement level character input system based on Chinese character separation , in particular to be suitable for the fields of Chinese character keyboard entry , handwriting input ( writing with a pen , writing with fingers and so on ) , information technology Chinese language ( character ) teaching , Chinese character retrieving , Chinese language word segmentation , pronunciation input , machine translation , intelligent search , etc . According to the principle that ancient and modern Chinese character strokes ( shape , quantity and order ) are absolutely respected , and the structures represented by ancient and modern Chinese characters are fully considered so as to conform to the word formation history of Chinese character to the greatest extent to finally be favor of solving a series of problems of Chinese character retrieving , teaching , inputting and the like , a certain Chinese character separation method is adopted and Chinese character substrate ration is realized , code fetch merging is carried on each substrate according to the pronunciation initial of the substrate ( or the located Chinese character thereof ) , the Chinese character is separated by using the separation method and the substrate , and the operations such as Chinese character keyboard and handwriting input , information technology Chinese language ( character ) teaching , informatization Chinese character retrieving , Chinese language word segmentation , pronunciation input , machine translation , intelligent search and the like at an intelligent statement level or at a non-statement level are performed in terms of a certain mode . A few of successful Chinese lexical analysis technologies are used to solve Chinese word segment- ation in a data fuse system for automatic processing information . The mixture of Boolean calculation AND and OR is regarded as the judgment regulation , which is simple and efficient . The invention relates to a one-stop type travel information searching method which is characterized by comprising the following steps : firstly , enabling users to input destination nouns through a transmission medium ; secondly , transmitting the destination nouns to a program server for Chinese word segmentation analyzing ; thirdly , enabling the program server to transmit the destination nouns to a user behavior analysis server to analyze the previous searching habits and behaviors of users ; and finally , drawing relative recommending information from a data base server and recommending the information to the users according to the results provided by the program server and the user behavior analysis server . Therefore , by performing effective Chinese word segmentation analyzing on the destination nouns input by the users , and simultaneously providing the most humanized travel information searching by matching with the user behavior analysis server , the problem of inaccurate user searching information is solved . Offline handwritten chinese character recognition ( HCCR ) is one of means for quick text input and it has a great demand in the area of file recognition , form processing , machine translation and office automation . However it still is a difficult task for handwritten chinese character recognition to put into practical use because of its large stroke change , writing anomaly , and no stroke ranking information can get , etc . al. An efficient classifier occupies very important position for increasing offline HCCR ratio . The recognition rate by currently used feature extraction methods and classifiers is far from the requirements of the people . For this problem , this study proposes a new feature extraction method for handwritten Chinese character recognition based on Kernel Independent Component Analysis ( KICA ) . Firstly , we extract independent basis images of handwritten Chinese character image and the projection vector by using KICA algorithm and then obtain the feature vector . This paper investigates the effects of unsupervised language model adaptation ( LMA ) in handwritten Chinese text recognition . For no prior information of recognition text is available , we use a two-pass recognition strategy . Recognition of handwritten Chinese characters is a large-scale pattern recognition task , which is difficult and time consuming to build the corresponding classifiers . In this paper , two feature selection methods are proposed to reduce the complexity and speed up the handwritten Chinese recognition : one is the ReliefF-Wrapper method which evaluates the original features with the ReliefF method , and then uses the wrapper method to decide the number of features to be selected ; and the other is GA-Wrapper that uses genetic algorithm to search the optimal subset of features with high training accuracy . Experiments were performed on 800 most frequently used Chinese characters , with 80,000 handwritten samples . Based on the SPDNN model , we constructed a three stage recognition system . The prototype system demonstrates a successful utilisation of SPDNN to similar handwritten Chinese recognition on the public database CCL/HCCRI ( 5401 characters /spl times/200 samples ) . Regarding the performance , the experiments on the CCL/HCCRI database demonstrated a 90.12 % of recognition accuracy with no rejection and 94.11 % of accuracy with 6.7 % rejection rates , respectively . In this paper , we propose a new framework of providing Handwritten Character Recognition as a Service ( HCRaaS ) via Internet , based on cloud computing technology . Using the proposed Cloud-based recognition platform , we would be able to apply many advanced algorithms in practice , such as modified quadratic discriminant function ( MQDF ) and SVM classifier used for large scale character recognition , writing adaptation technology , and handwriting Chinese word/text line recognition that usually involve large storage and computation cost . With the merits and characteristics of HCRaaS , users of different mobile devices are not only no longer subject to local computing capacity and storage resource constraints , but also , they can benefit from higher recognition accuracy and personalized service with low hardware costs . In this paper , we propose a hybrid language model for handwritten Chinese sentence recognition . This hybrid model is integrated from several independent language models , each of which is trained from a distinct type of corpus and models specifically the linguistic behavior for that type of corpus . Handwritten Chinese text recognition characters is a challenging problem as it involves a imbalanced training data , and the samples are very different even in same character . In this paper , we propose a novel algorithm based on the bidirectional Recurrent Neural Network ( BiRNN ) to recognize the characters in the text regions . The first part of the book covers both widespread canonical algorithms to a reliable recognizer and newly developed scalable methods in Chinese handwriting recognition . The recognition of Chinese handwritten text is presented systematically , including instructive guidelines for collecting samples , novel recognition paradigms , distributed discriminative learning of appearance models and distributed estimation of contextual models for large categories , in addition to celebrated methods , e.g. Gradient features , MQDF and HMMs . In the second part of this book , endeavors are made to create a friendlier human-machine interface through application of Chinese handwriting recognition . The final section presents the most studied aspect of the Chinese language , the phonetic consistency or regularity , and , in addition , brings to readers ' attention another aspect of the Chinese language , the semantic consistency which is equally important but has so far been neglected . This paper provides useful information for readers in Chinese ... This article is devoted to the research of the Chinese image as a model created by the American mass-media . The author studies one of the most significant themes titled “ Chinese Currency Manipulation ” . The author singles out the leading methods of semantization and suggests the lexical analysis of the described information model . Offline Chinese characters segmentation is one of the most difficult problems in Chinese character recognition , because handwritten Chinese characters have deformations , connected strokes and overlapped characters , and they often occurre with punctuations and digital numrbers . The multi-step offline handwritten Chinese characters segmentation method based on adaptive genetic algorithm was put forward in this paper to segment connected or overlaps characters , punctuations and digital numbers . Furthermore , the system is a kind of mobile and convenient supervising tool to service official veterinarian to carry out their work . Finally , with the TDSCDMA technology prevalence and communication fee decrease , the system will take part in a important role in constructing Chinese pork quality safety traceability system . This paper concentrates on syntactic reordering of predicate-predicate patterns in Chinese dependency trees through contrastively analyzing construction types in Chinese and their corresponding translations in Korean . We explore useful linguistic knowledge that assists effective syntactic reordering of Chinese dependency trees ; we design two experiments with different kinds of linguistic knowledge combined with the phraseand hierarchical phrase-based SMT systems , and assess the effectiveness of our proposed methods . The experiments achieved significant improvements by resolving the long-distance reordering problem . Text is an important modality for human-computer interaction , so studying the relationship between natural language and affective information as well as assessing the underpinned affective qualities of natural language has been the focus of research community . Several approaches have been performed to sense affect from English text , but the study on Chinese text emotion detection is still at the beginning . In this paper , we devote ourselves to sensing affective information from Chinese documents with the aim to group those into a set of emotions . Two experiments manipulating neighborhood size and word frequency were used to investigate the lexical processing of Chinese words . The neighborhood size of a word is defined as the number of two-character words sharing the same initial constituent character . The reconstruction of Chinese teaching content has become the core problem of new Chinese curriculum and instruction , which is composed of the reconstruction of Chinese textbooks and creative production of Chinese instruction , and is mainly reflected from the following three aspects : self-understanding of the context , knowledge selection and transmission , production and change of Chinese experience . Three questions in the reconstruction of Chinese instructional content to which must be paid attention are how to design problem situation , how to acquire multi-interpretation of context , and how to view upon the incorrect reply of students . The proposed model is able to not only encode the long-distance dependencies but also capture the functional similarities for better translation prediction ( i.e. , ambiguous words translation and word forms translation ) . Examined by a largescale Chinese-English translation task , the proposed approach achieves a significant improvement ( of up to + 1.9 BLEU points ) over the baseline system , and meanwhile outperforms a number of context-enhanced comparison system . When involving pronouns , Chinese verb phrase(namely VP ) ellipsis constructions will be ambiguous , and ambiguity is a significant feature of VP ellipsis constructions . Chinese VP ellipsis constructions in both coordinate sentences and relative clauses exhibit analogous properties . Sentences containing VP ellipsis that involves one pronoun show strict and sloppy interpretation ambiguity;sentences contain two or more pronouns in VP ellipsis constructions have mixed readings in addition to strict and sloppy readings . The implementation error affected both the generative and discriminative RNNGs . We summarize corrected English phrase - structure PTB § 23 parsing result in Table [ reference ] , Chinese ( CTB 5.1 § 271–300 ) in Table [ reference ] ( achieving the the best reported result on both datasets ) , and English and Chinese language modeling perplexities in Table [ reference ] . The considerable improvement in parsing accuracy indicates that properly composing the constituent and propagating information upwards is crucial . subsection : Chinese characters Compared to Latin character recognition , isolated Chinese character recognition is a much harder problem , mainly because of the much larger category set , but also because of wide variability of writing styles , and the confusion between similar characters . We use a dataset from the Institute of Automation of Chinese Academy of Sciences ( CASIA ) , which contains 300 samples for each of 3755 characters ( in GB1 set ) . In an extension to this work , chopra used a similar convolutional model for the encoder , but replaced the decoder with an RNN , producing further improvement in performance on both datasets . In another paper that is closely related to our work , hu:2015:EMNLP introduce a large dataset for Chinese short text summarization . They show promising results on their Chinese dataset using an encoder - decoder RNN , but do not report experiments on English corpora . A deterministic algorithm for reconstructing off-line calligraphical strokes with priority rules - D Hung & J Cheng . Off-line handwritten Chinese character recognition based on structural features and fuzzy ARTMAP - N Murshed , A Amin & S Singh . Agent-based text extraction from pyramid images - C Tan , B Yuan & C Ang.- PATTERN RECOGNITION : Vector quantization and minimum description length - H Bischof & A Leonardis . Recently , an effective segmentation-free approach via deep neural network based hidden Markov model ( DNN-HMM ) was proposed and successfully applied to offline handwritten Chinese text recognition . In this study , to further improve the modeling capability , we adopt deep convolutional neural networks ( DCNN ) to calculate the HMM state posteriors . The segmentation of text into characters was rarely discussed . The segmentation is an important preprocess of the off-line Chinese character recognition because correct recognition of characters relies on correct segmentation of characters . In handwritten Chinese characters , characters may be written to touch each other or to overlap with each other , therefore , the segmentation problem is not an easy one . A Chinese handwriting database named HIT-MW is presented to facilitate the offline Chinese handwritten text recognition . Both the writers and the texts for handcopying are carefully sampled with a ... A Chinese handwriting database named HIT-MW is presented to facilitate the offline Chinese handwritten text recognition . Both the writers and the texts for handcopying are carefully sampled with a systematic scheme . Offline Chinese handwritten character string recognition is one of the most important research fields in pattern recognition . Due to the free writing style , large variability in character shapes and different geometric characteristics , Chinese handwritten character string recognition is a challenging problem to deal with . We compare three representative modeling approaches , namely the multiple-prototype-based template matching approach , the subspace approach and the continuous density hidden Markov model approach for large vocabulary , offline recognition of handwritten Chinese characters . On a task of classification of 4616 handwritten Chinese characters , we evaluate and compare the strength and weakness of individual approaches in terms of the classification accuracy , the memory requirement and the computational complexity . We train following DNN , 1x48x48 - 100C3 - MP2 - 200C2 - MP2 - 300C2 - MP2 - 400C2 - MP2 - 500N - 3755N , on offline as well as on online characters . For the offline character recognition task , we resize all characters to 40x40 pixels and place them in the center of a 48x48 image . The contrast of each image is normalized independently . Previous approaches to Chinese zero pronoun resolution mainly use syntactic information and probabilistic methods , but the context information is ignored . To make full use of the context and semantic information , we build a context-aware model . This paper investigates the problem of Chinese zero pronoun resolution . Most existing approaches are based on machine learning algorithms , using hand-crafted features , which is labor-intensive . While pronoun resolution in both languages remains a challenging task , Chinese pronoun resolution is further complicated by ( 1 ) the lack of publicly available Chinese word lists or dictionaries that can be used to look up essential mention attributes such as gender and number ; and ( 2 ) the relative dearth of Chinese coreference-annotated data . Existing approaches to Chinese pronoun resolution are monolingual , training and testing a pronoun resolver on Chinese data . In contrast , we propose a bilingual approach to Chinese pronoun resolution , aiming to improve the resolution of Chinese pronouns by leveraging the publicly available English dictionaries and coreference annotations . Then , the overall structure , module design and system display of the system were introduced in detail , and pronoun resolution and omission recovery module were explained . In practice , the long-term and short-term memory network model learning suitable for serialization input was used to express the deep characteristics of the context and applied to the Chinese pronoun resolution and omission recovery tasks respectively . In addition , the effectiveness of the Chinese pronoun disambiguation technology and the pronoun ellipsis recovery technology in the intelligent robot system was discussed , and a targeted analysis and optimization of the semantic complement task were made . This indicates the critical role of the structural information in zero anaphora resolution and the necessity of tree kernel-based methods in modeling such structural information . To our best knowledge , this is the first systematic work dealing with all the three sub-tasks in Chinese zero anaphora resolution via a unified framework . Moreover , we release a Chinese zero anaphora corpus of 100 documents , which adds a layer of annotation to the manually-parsed sentences in the Chinese Treebank ( CTB ) 6.0 . State-of-the-art Chinese zero pronoun resolution systems are supervised , thus relying on training data containing manually resolved zero pronouns . To eliminate the reliance on annotated data , we present a generative model for unsupervised Chinese zero pronoun resolution . At the core of our model is a novel hypothesis : a probabilistic pronoun resolver trained on overt pronouns in an unsupervised manner can be used to resolve zero pronouns .
Then the attribute words in the test QA pairs can be used to calculate the matching scores . The experimental results show that the proposed representation method of QA patterns has good flexibility to deal with the uncertainty caused by the Chinese word segmentation , and the proposed method has good performance at both MAP and MRR on the test data .
In the text mining , the technology of Chinese automatic word segmentation is a difficult problem that the computer science has to face . Aiming at the characteristics of Chinese writing , such as no space between words , continuous writing in sentences and difficulty of segmenting the ambiguous words , the grammatical phenomena are summarized which lie in the typical ambiguity , and the codes library of different parts of speech used for coding is built up .
As one of the important problem in the field of Chinese automatic word segmentation and Chinese information process , part of speech tagging is the research difficulty and emphases in the filed . The precision of POS tagging to syntactic category has influenced badly the quality of POS tagging .
Identifying Textual Entailment is the task of finding the relationship between the given hypothesis and text fragments . Developing a high-performance text paraphrasing system usually requires rich external knowledge such as syntactic parsing , thesaurus which is limited in Chinese since the Chinese word segmentation problem should be resolve first . By following last year , in this year , we continue adopting the created RITE system and combine with multiple online available thesaurus .
For the Chinese word segmentation problem the BP algorithm has relatively slow convergence speed . Here the Levenbery-Marquart algorithm is introduced to optimize the Chinese word segmentation system based on the neural network .
According to the features of Chinese documents , this paper designs and implements the Chinese Text Clustering System to perform automatic clustering of Chinese documents . Firstly , this system will carry out Chinese word automatic segmentation for the input Chinese document sets by using reverse maximum matching method . Secondly , further text preprocessing is performed .
In order to identify new words in huge Chinese corpus efficiently , this paper comes up with an algorithm based on ensemble methods . At first we perform Chinese word segmenting with Trie and build segment-tree . Then we select words pattern drawing method , frequency filtering , independent word probability and naive Bayes model to be sub-models of ensemble methods and train them independently .
The invention discloses an intelligent statement level character input system based on Chinese character separation , in particular to be suitable for the fields of Chinese character keyboard entry , handwriting input ( writing with a pen , writing with fingers and so on ) , information technology Chinese language ( character ) teaching , Chinese character retrieving , Chinese language word segmentation , pronunciation input , machine translation , intelligent search , etc . According to the principle that ancient and modern Chinese character strokes ( shape , quantity and order ) are absolutely respected , and the structures represented by ancient and modern Chinese characters are fully considered so as to conform to the word formation history of Chinese character to the greatest extent to finally be favor of solving a series of problems of Chinese character retrieving , teaching , inputting and the like , a certain Chinese character separation method is adopted and Chinese character substrate ration is realized , code fetch merging is carried on each substrate according to the pronunciation initial of the substrate ( or the located Chinese character thereof ) , the Chinese character is separated by using the separation method and the substrate , and the operations such as Chinese character keyboard and handwriting input , information technology Chinese language ( character ) teaching , informatization Chinese character retrieving , Chinese language word segmentation , pronunciation input , machine translation , intelligent search and the like at an intelligent statement level or at a non-statement level are performed in terms of a certain mode .
A few of successful Chinese lexical analysis technologies are used to solve Chinese word segment- ation in a data fuse system for automatic processing information . The mixture of Boolean calculation AND and OR is regarded as the judgment regulation , which is simple and efficient .
The invention relates to a one-stop type travel information searching method which is characterized by comprising the following steps : firstly , enabling users to input destination nouns through a transmission medium ; secondly , transmitting the destination nouns to a program server for Chinese word segmentation analyzing ; thirdly , enabling the program server to transmit the destination nouns to a user behavior analysis server to analyze the previous searching habits and behaviors of users ; and finally , drawing relative recommending information from a data base server and recommending the information to the users according to the results provided by the program server and the user behavior analysis server . Therefore , by performing effective Chinese word segmentation analyzing on the destination nouns input by the users , and simultaneously providing the most humanized travel information searching by matching with the user behavior analysis server , the problem of inaccurate user searching information is solved .
Offline handwritten chinese character recognition ( HCCR ) is one of means for quick text input and it has a great demand in the area of file recognition , form processing , machine translation and office automation . However it still is a difficult task for handwritten chinese character recognition to put into practical use because of its large stroke change , writing anomaly , and no stroke ranking information can get , etc . al. An efficient classifier occupies very important position for increasing offline HCCR ratio .
The recognition rate by currently used feature extraction methods and classifiers is far from the requirements of the people . For this problem , this study proposes a new feature extraction method for handwritten Chinese character recognition based on Kernel Independent Component Analysis ( KICA ) . Firstly , we extract independent basis images of handwritten Chinese character image and the projection vector by using KICA algorithm and then obtain the feature vector .
This paper investigates the effects of unsupervised language model adaptation ( LMA ) in handwritten Chinese text recognition . For no prior information of recognition text is available , we use a two-pass recognition strategy .
Recognition of handwritten Chinese characters is a large-scale pattern recognition task , which is difficult and time consuming to build the corresponding classifiers . In this paper , two feature selection methods are proposed to reduce the complexity and speed up the handwritten Chinese recognition : one is the ReliefF-Wrapper method which evaluates the original features with the ReliefF method , and then uses the wrapper method to decide the number of features to be selected ; and the other is GA-Wrapper that uses genetic algorithm to search the optimal subset of features with high training accuracy . Experiments were performed on 800 most frequently used Chinese characters , with 80,000 handwritten samples .
Based on the SPDNN model , we constructed a three stage recognition system . The prototype system demonstrates a successful utilisation of SPDNN to similar handwritten Chinese recognition on the public database CCL/HCCRI ( 5401 characters /spl times/200 samples ) . Regarding the performance , the experiments on the CCL/HCCRI database demonstrated a 90.12 % of recognition accuracy with no rejection and 94.11 % of accuracy with 6.7 % rejection rates , respectively .
In this paper , we propose a new framework of providing Handwritten Character Recognition as a Service ( HCRaaS ) via Internet , based on cloud computing technology . Using the proposed Cloud-based recognition platform , we would be able to apply many advanced algorithms in practice , such as modified quadratic discriminant function ( MQDF ) and SVM classifier used for large scale character recognition , writing adaptation technology , and handwriting Chinese word/text line recognition that usually involve large storage and computation cost . With the merits and characteristics of HCRaaS , users of different mobile devices are not only no longer subject to local computing capacity and storage resource constraints , but also , they can benefit from higher recognition accuracy and personalized service with low hardware costs .
In this paper , we propose a hybrid language model for handwritten Chinese sentence recognition . This hybrid model is integrated from several independent language models , each of which is trained from a distinct type of corpus and models specifically the linguistic behavior for that type of corpus .
Handwritten Chinese text recognition characters is a challenging problem as it involves a imbalanced training data , and the samples are very different even in same character . In this paper , we propose a novel algorithm based on the bidirectional Recurrent Neural Network ( BiRNN ) to recognize the characters in the text regions .
The first part of the book covers both widespread canonical algorithms to a reliable recognizer and newly developed scalable methods in Chinese handwriting recognition . The recognition of Chinese handwritten text is presented systematically , including instructive guidelines for collecting samples , novel recognition paradigms , distributed discriminative learning of appearance models and distributed estimation of contextual models for large categories , in addition to celebrated methods , e.g. Gradient features , MQDF and HMMs . In the second part of this book , endeavors are made to create a friendlier human-machine interface through application of Chinese handwriting recognition .
The final section presents the most studied aspect of the Chinese language , the phonetic consistency or regularity , and , in addition , brings to readers ' attention another aspect of the Chinese language , the semantic consistency which is equally important but has so far been neglected . This paper provides useful information for readers in Chinese ...
This article is devoted to the research of the Chinese image as a model created by the American mass-media . The author studies one of the most significant themes titled “ Chinese Currency Manipulation ” . The author singles out the leading methods of semantization and suggests the lexical analysis of the described information model .
Offline Chinese characters segmentation is one of the most difficult problems in Chinese character recognition , because handwritten Chinese characters have deformations , connected strokes and overlapped characters , and they often occurre with punctuations and digital numrbers . The multi-step offline handwritten Chinese characters segmentation method based on adaptive genetic algorithm was put forward in this paper to segment connected or overlaps characters , punctuations and digital numbers .
Furthermore , the system is a kind of mobile and convenient supervising tool to service official veterinarian to carry out their work . Finally , with the TDSCDMA technology prevalence and communication fee decrease , the system will take part in a important role in constructing Chinese pork quality safety traceability system .
This paper concentrates on syntactic reordering of predicate-predicate patterns in Chinese dependency trees through contrastively analyzing construction types in Chinese and their corresponding translations in Korean . We explore useful linguistic knowledge that assists effective syntactic reordering of Chinese dependency trees ; we design two experiments with different kinds of linguistic knowledge combined with the phraseand hierarchical phrase-based SMT systems , and assess the effectiveness of our proposed methods . The experiments achieved significant improvements by resolving the long-distance reordering problem .
Text is an important modality for human-computer interaction , so studying the relationship between natural language and affective information as well as assessing the underpinned affective qualities of natural language has been the focus of research community . Several approaches have been performed to sense affect from English text , but the study on Chinese text emotion detection is still at the beginning . In this paper , we devote ourselves to sensing affective information from Chinese documents with the aim to group those into a set of emotions .
Two experiments manipulating neighborhood size and word frequency were used to investigate the lexical processing of Chinese words . The neighborhood size of a word is defined as the number of two-character words sharing the same initial constituent character .
The reconstruction of Chinese teaching content has become the core problem of new Chinese curriculum and instruction , which is composed of the reconstruction of Chinese textbooks and creative production of Chinese instruction , and is mainly reflected from the following three aspects : self-understanding of the context , knowledge selection and transmission , production and change of Chinese experience . Three questions in the reconstruction of Chinese instructional content to which must be paid attention are how to design problem situation , how to acquire multi-interpretation of context , and how to view upon the incorrect reply of students .
The proposed model is able to not only encode the long-distance dependencies but also capture the functional similarities for better translation prediction ( i.e. , ambiguous words translation and word forms translation ) . Examined by a largescale Chinese-English translation task , the proposed approach achieves a significant improvement ( of up to + 1.9 BLEU points ) over the baseline system , and meanwhile outperforms a number of context-enhanced comparison system .
When involving pronouns , Chinese verb phrase(namely VP ) ellipsis constructions will be ambiguous , and ambiguity is a significant feature of VP ellipsis constructions . Chinese VP ellipsis constructions in both coordinate sentences and relative clauses exhibit analogous properties . Sentences containing VP ellipsis that involves one pronoun show strict and sloppy interpretation ambiguity;sentences contain two or more pronouns in VP ellipsis constructions have mixed readings in addition to strict and sloppy readings .
The implementation error affected both the generative and discriminative RNNGs . We summarize corrected English phrase - structure PTB § 23 parsing result in Table [ reference ] , Chinese ( CTB 5.1 § 271–300 ) in Table [ reference ] ( achieving the the best reported result on both datasets ) , and English and Chinese language modeling perplexities in Table [ reference ] . The considerable improvement in parsing accuracy indicates that properly composing the constituent and propagating information upwards is crucial .
subsection : Chinese characters Compared to Latin character recognition , isolated Chinese character recognition is a much harder problem , mainly because of the much larger category set , but also because of wide variability of writing styles , and the confusion between similar characters . We use a dataset from the Institute of Automation of Chinese Academy of Sciences ( CASIA ) , which contains 300 samples for each of 3755 characters ( in GB1 set ) .
In an extension to this work , chopra used a similar convolutional model for the encoder , but replaced the decoder with an RNN , producing further improvement in performance on both datasets . In another paper that is closely related to our work , hu:2015:EMNLP introduce a large dataset for Chinese short text summarization . They show promising results on their Chinese dataset using an encoder - decoder RNN , but do not report experiments on English corpora .
A deterministic algorithm for reconstructing off-line calligraphical strokes with priority rules - D Hung & J Cheng . Off-line handwritten Chinese character recognition based on structural features and fuzzy ARTMAP - N Murshed , A Amin & S Singh . Agent-based text extraction from pyramid images - C Tan , B Yuan & C Ang.- PATTERN RECOGNITION : Vector quantization and minimum description length - H Bischof & A Leonardis .
Recently , an effective segmentation-free approach via deep neural network based hidden Markov model ( DNN-HMM ) was proposed and successfully applied to offline handwritten Chinese text recognition . In this study , to further improve the modeling capability , we adopt deep convolutional neural networks ( DCNN ) to calculate the HMM state posteriors .
The segmentation of text into characters was rarely discussed . The segmentation is an important preprocess of the off-line Chinese character recognition because correct recognition of characters relies on correct segmentation of characters . In handwritten Chinese characters , characters may be written to touch each other or to overlap with each other , therefore , the segmentation problem is not an easy one .
A Chinese handwriting database named HIT-MW is presented to facilitate the offline Chinese handwritten text recognition . Both the writers and the texts for handcopying are carefully sampled with a ...
A Chinese handwriting database named HIT-MW is presented to facilitate the offline Chinese handwritten text recognition . Both the writers and the texts for handcopying are carefully sampled with a systematic scheme .
Offline Chinese handwritten character string recognition is one of the most important research fields in pattern recognition . Due to the free writing style , large variability in character shapes and different geometric characteristics , Chinese handwritten character string recognition is a challenging problem to deal with .
We compare three representative modeling approaches , namely the multiple-prototype-based template matching approach , the subspace approach and the continuous density hidden Markov model approach for large vocabulary , offline recognition of handwritten Chinese characters . On a task of classification of 4616 handwritten Chinese characters , we evaluate and compare the strength and weakness of individual approaches in terms of the classification accuracy , the memory requirement and the computational complexity .
We train following DNN , 1x48x48 - 100C3 - MP2 - 200C2 - MP2 - 300C2 - MP2 - 400C2 - MP2 - 500N - 3755N , on offline as well as on online characters . For the offline character recognition task , we resize all characters to 40x40 pixels and place them in the center of a 48x48 image . The contrast of each image is normalized independently .
Previous approaches to Chinese zero pronoun resolution mainly use syntactic information and probabilistic methods , but the context information is ignored . To make full use of the context and semantic information , we build a context-aware model .
This paper investigates the problem of Chinese zero pronoun resolution . Most existing approaches are based on machine learning algorithms , using hand-crafted features , which is labor-intensive .
While pronoun resolution in both languages remains a challenging task , Chinese pronoun resolution is further complicated by ( 1 ) the lack of publicly available Chinese word lists or dictionaries that can be used to look up essential mention attributes such as gender and number ; and ( 2 ) the relative dearth of Chinese coreference-annotated data . Existing approaches to Chinese pronoun resolution are monolingual , training and testing a pronoun resolver on Chinese data . In contrast , we propose a bilingual approach to Chinese pronoun resolution , aiming to improve the resolution of Chinese pronouns by leveraging the publicly available English dictionaries and coreference annotations .
Then , the overall structure , module design and system display of the system were introduced in detail , and pronoun resolution and omission recovery module were explained . In practice , the long-term and short-term memory network model learning suitable for serialization input was used to express the deep characteristics of the context and applied to the Chinese pronoun resolution and omission recovery tasks respectively . In addition , the effectiveness of the Chinese pronoun disambiguation technology and the pronoun ellipsis recovery technology in the intelligent robot system was discussed , and a targeted analysis and optimization of the semantic complement task were made .
This indicates the critical role of the structural information in zero anaphora resolution and the necessity of tree kernel-based methods in modeling such structural information . To our best knowledge , this is the first systematic work dealing with all the three sub-tasks in Chinese zero anaphora resolution via a unified framework . Moreover , we release a Chinese zero anaphora corpus of 100 documents , which adds a layer of annotation to the manually-parsed sentences in the Chinese Treebank ( CTB ) 6.0 .
State-of-the-art Chinese zero pronoun resolution systems are supervised , thus relying on training data containing manually resolved zero pronouns . To eliminate the reliance on annotated data , we present a generative model for unsupervised Chinese zero pronoun resolution . At the core of our model is a novel hypothesis : a probabilistic pronoun resolver trained on overt pronouns in an unsupervised manner can be used to resolve zero pronouns .
Discernibility Matrix and Rules Acquisition Based Chinese Question Answering System Research on ambiguous words segmentation algorithm based on improved BP neural network A Method of POS Tagging Based on Priority of Rules Combining Multiple Lexical Resources for Chinese Textual Entailment Recognition Optimization of Chinese word segmentation based on neural network Design and Implementation of Chinese Text Clustering System New Words Identification Based on Ensemble Methods Intelligent statement level character input system based on Chinese character separation Application of Chinese Lexical Analysis Technology in Information Engineering One-stop type travel information searching method Handwritten Chinese character recognition based on SVM with hybrid kernel function Research on Feature Extraction Method for Handwritten Chinese Character Recognition Based on Kernel Independent Component Analysis Improving Handwritten Chinese Text Recognition by Unsupervised Language Model Adaptation Feature selection in recognition of handwritten Chinese characters Recognition of handwritten similar Chinese characters by self-growing probabilistic decision-based neural networks Handwriting Character Recognition as a Service: A New Handwriting Recognition System Based on Cloud Computing A Hybrid Language Model for Handwritten Chinese Sentence Recognition An Algorithm of Bidirectional RNN for Offline Handwritten Chinese Text Recognition Chinese Handwriting Recognition: An Algorithmic Perspective An overview of the characteristics of the Chinese writing system Candidate of Philology, Assistant Professor Chair of Foreign Languages Institute of Fundamental Training Multi-step Offline Handwritten Chinese Characters Segmentation with GA Traceability System of Pig-Raising Process and Quality Safety on 3G Chinese Syntactic Reordering through Contrastive Analysis of Predicate-predicate Patterns in Chinese-to-Korean SMT A Rough Set and SVM Based Approach to Chinese Textual Affect Sensing Neighborhood Size Effects of Chinese Words in Lexical Decision and Reading Thinking on the Reconstruction of Chinese Teaching Content Translation Prediction with Source Dependency-Based Context Representation Features of Semantic Ambiguity in Chinese VP Ellipsis Constructions Recurrent Neural Network Grammars Multi-column deep neural networks for image classification Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond International Conference on Advances in Pattern Recognition: Proceedings of ICAPR '98, 23-25 November 1998, Plymouth, UK Deep Convolutional Neural Network Based Hidden Markov Model for Offline Handwritten Chinese Text Recognition A new method for segmenting handwritten Chinese characters Corpus-based HIT-MW database for offline recognition of general-purpose Chinese handwritten text Corpus-based HIT-MW database for offline recognition of general-purpose Chinese handwritten text Post processing for offline Chinese handwritten character string recognition A comparative study of several modeling approaches for large vocabulary offline recognition of handwritten Chinese characters Multi-column deep neural networks for image classification A Context-Aware Model Using Distributed Representations for Chinese Zero Pronoun Resolution A Deep Neural Network for Chinese Zero Pronoun Resolution Chinese Overt Pronoun Resolution: A Bilingual Approach Exploration of WeChat-based Legal Robot A Tree Kernel-Based Unified Framework for Chinese Zero Anaphora Resolution Chinese Zero Pronoun Resolution: An Unsupervised Probabilistic Model Rivaling Supervised Resolvers
3990905465180073aa0b81e436a2255ae65972cb 26e530304b3bce2d3a5b1d77c8a44d21a9909c10 778a8417b81c1ef1d9b28f10e280378e0fee46dd c25ec33794e429a4f107d8dad33403d9ef516eda 09f2dcc3606fa29076c4f9c1f58577ce38ea735c 2441d49c8ce4b3eb3d38028e3d1c2811f21b73b3 0d718ba007f1ba2378854776ef283881990b8423 5921ffdd00fd0ae8232ea746f845bf1f266a837c f3912ffba2b3be79debf5b3d95140de912ec78c4 1abb8b574795c0d2295858a29be38ed9bbb4ce8a 7d9690bce7016715c397114404a169b9dcf5b37e c7e0ad60f9717255b487422dbd3cbe0f48d902df a4787b1d437ea880818956ba91b39810de5d2ddb 57cb2fe7046f1d9dcfdc39b6b5e325b4bbac1e82 58ebef9104b4878231d6681300857a57d396bbce c334053185ad2b71393d6db897550183af2480a3 ae6e799e96068d2c11c6a2718963f6736c8b15be c5d929d600430f1395e7f0b1823d441091fc6e37 952cad8e15e8b5c33699bdfa13aba0def168a269 77bca79e0b2352d45ce847d70c2182f463c8bfa1 8e06b9fa4ead5c98c78f604040362b7ddeaf194a b5e9ede48501309a0b8d804692d1d7f0a3cd57b2 a8dfbbc66dd9f39b857a9513371f40dffbc6b9cc d38b2a1393fb6cca613dc4d33ea41a2efe6173ee 5d8b9f8a8f110143961d31de18d0816af8eb6033 3c29022d925860f2ff05ddd8f12c7a129673623a 5dfb927a22a093123f0e8c8f0750e6d6c0fa4f39 daf5a9a464c31ea5428cc312419403850e11be2a 83385f49fe86aab67f3981a4c8c4927984b1d3b0 4f535956224caa19cca248ac2b8572da8938a35a 262532e75ed9af896e5e9d84b465b561e2962306 70675a12b0022a1683206d0ff2883868b5c06253 4c0fc2639d7bc67e78154744202b179696f204fa 960ef34612a05771fec5eb7db01fc33a70ad4759 082aa807ee84ef30df393fbb4d712f949e993376 51786cce627ad82bdb0118bc11989768bbbb9286 9e68b730684f4f91b3d3aec05ed0b9f4994066dc 8b95b492a87d0bf232be53a55d5d79e9d0916f57 b057b85f603d935a05db554434fdc0da62f6c90f c19662504b30c6577010899f6be14206940e9e87 796ac24ba1d670acc6ec4126d908f172edfb1ead 293453697cecd4ceda63b6875751e374b4730a42
["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Engineering","Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Engineering","Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"]
2017 2007 2008 2013 2006 2009 2014 2010 2007 2011 2005 2013 2012 2002 1998 2011 2012 2019 2013 1996 2010 2009 2011 2010 2008 2006 2009 2017 2009 2016 2012 2016 2011 2017 1997 2007 2007 2012 2002 2012 2016 2016 2014 2018 2010 2014
IJCRS (1) NTCIR NCM Document Analysis Systems ICDAR ICFHR ICIC (3) ICFIE CCTA (1) ISDA (1) AAAI HLT-NAACL 2012 IEEE Conference on Computer Vision and Pattern Recognition CoNLL ACPR ICDAR DRR ICPR (3) 2012 IEEE Conference on Computer Vision and Pattern Recognition ICYCSEE (1) AAAI EMNLP EMNLP
https://api.semanticscholar.org/3990905465180073aa0b81e436a2255ae65972cb https://api.semanticscholar.org/26e530304b3bce2d3a5b1d77c8a44d21a9909c10 https://api.semanticscholar.org/778a8417b81c1ef1d9b28f10e280378e0fee46dd https://api.semanticscholar.org/c25ec33794e429a4f107d8dad33403d9ef516eda https://api.semanticscholar.org/09f2dcc3606fa29076c4f9c1f58577ce38ea735c https://api.semanticscholar.org/2441d49c8ce4b3eb3d38028e3d1c2811f21b73b3 https://api.semanticscholar.org/0d718ba007f1ba2378854776ef283881990b8423 https://api.semanticscholar.org/5921ffdd00fd0ae8232ea746f845bf1f266a837c https://api.semanticscholar.org/f3912ffba2b3be79debf5b3d95140de912ec78c4 https://api.semanticscholar.org/1abb8b574795c0d2295858a29be38ed9bbb4ce8a https://api.semanticscholar.org/7d9690bce7016715c397114404a169b9dcf5b37e https://api.semanticscholar.org/c7e0ad60f9717255b487422dbd3cbe0f48d902df https://api.semanticscholar.org/a4787b1d437ea880818956ba91b39810de5d2ddb https://api.semanticscholar.org/57cb2fe7046f1d9dcfdc39b6b5e325b4bbac1e82 https://api.semanticscholar.org/58ebef9104b4878231d6681300857a57d396bbce https://api.semanticscholar.org/c334053185ad2b71393d6db897550183af2480a3 https://api.semanticscholar.org/ae6e799e96068d2c11c6a2718963f6736c8b15be https://api.semanticscholar.org/c5d929d600430f1395e7f0b1823d441091fc6e37 https://api.semanticscholar.org/952cad8e15e8b5c33699bdfa13aba0def168a269 https://api.semanticscholar.org/77bca79e0b2352d45ce847d70c2182f463c8bfa1 https://api.semanticscholar.org/8e06b9fa4ead5c98c78f604040362b7ddeaf194a https://api.semanticscholar.org/b5e9ede48501309a0b8d804692d1d7f0a3cd57b2 https://api.semanticscholar.org/a8dfbbc66dd9f39b857a9513371f40dffbc6b9cc https://api.semanticscholar.org/d38b2a1393fb6cca613dc4d33ea41a2efe6173ee https://api.semanticscholar.org/5d8b9f8a8f110143961d31de18d0816af8eb6033 https://api.semanticscholar.org/3c29022d925860f2ff05ddd8f12c7a129673623a https://api.semanticscholar.org/5dfb927a22a093123f0e8c8f0750e6d6c0fa4f39 https://api.semanticscholar.org/daf5a9a464c31ea5428cc312419403850e11be2a https://api.semanticscholar.org/83385f49fe86aab67f3981a4c8c4927984b1d3b0 https://www.semanticscholar.org/paper/7345843e87c81e24e42264859b214d26042f8d51 https://www.semanticscholar.org/paper/398c296d0cc7f9d180f84969f8937e6d3a413796 https://www.semanticscholar.org/paper/f37076f426023241f19cdc2fb0a0fd733a6fa7fa https://api.semanticscholar.org/4f535956224caa19cca248ac2b8572da8938a35a https://api.semanticscholar.org/262532e75ed9af896e5e9d84b465b561e2962306 https://api.semanticscholar.org/70675a12b0022a1683206d0ff2883868b5c06253 https://api.semanticscholar.org/4c0fc2639d7bc67e78154744202b179696f204fa https://api.semanticscholar.org/960ef34612a05771fec5eb7db01fc33a70ad4759 https://api.semanticscholar.org/082aa807ee84ef30df393fbb4d712f949e993376 https://api.semanticscholar.org/51786cce627ad82bdb0118bc11989768bbbb9286 https://www.semanticscholar.org/paper/398c296d0cc7f9d180f84969f8937e6d3a413796 https://api.semanticscholar.org/9e68b730684f4f91b3d3aec05ed0b9f4994066dc https://api.semanticscholar.org/8b95b492a87d0bf232be53a55d5d79e9d0916f57 https://api.semanticscholar.org/b057b85f603d935a05db554434fdc0da62f6c90f https://api.semanticscholar.org/c19662504b30c6577010899f6be14206940e9e87 https://api.semanticscholar.org/796ac24ba1d670acc6ec4126d908f172edfb1ead https://api.semanticscholar.org/293453697cecd4ceda63b6875751e374b4730a42