Existing Chinese named entity recognition(NER)research utilises 1D lexicon-based sequence labelling frameworks,which can only recognise flat entities.While lexicons serve as prior knowledge and enhance semantic inform...Existing Chinese named entity recognition(NER)research utilises 1D lexicon-based sequence labelling frameworks,which can only recognise flat entities.While lexicons serve as prior knowledge and enhance semantic information,they also pose completeness and resource requirements limitations.This paper proposes a template-based classification(TC)model to avoid lexicon issues and to identify nested entities.Template-based classification provides a template word for each entity type,which utilises contrastive learning to integrate the common characteristics among entities with the same category.Contrastive learning makes template words the centre points of their category in the vector space,thus improving generalisation ability.Additionally,TC presents a 2D tablefilling label scheme that classifies entities based on the attention distribution of template words.The proposed novel decoder algorithm enables TC recognition of both flat and nested entities simultaneously.Experimental results show that TC achieves the state-ofthe-art performance on five Chinese datasets.展开更多
The study employs the theoretical framework of Nanosyntax to analyze the generative mechanism of verbal ABAB reduplication pattern in Mandarin Chinese.The research characterizes ABAB reduplication as an inflectional o...The study employs the theoretical framework of Nanosyntax to analyze the generative mechanism of verbal ABAB reduplication pattern in Mandarin Chinese.The research characterizes ABAB reduplication as an inflectional operation involving functional projections of pluractionality and aspect.It distinguishes between event-internal and event-external pluralization,as well as inner and outer aspect in verbal reduplication.Following the One-Function-One-Head Principle in Nanosyntax,verbal ABAB form occurs through the merging of categoryless roots that are categorized by little v,with the RED affix syncretizing multiple functional morphemes.This framework reduces lexical burden and precisely represents the unique syntactic structure of Chinese verbal reduplication.展开更多
This study examines the “V + Dào” construction as a state change event through the lens of the Event Integration Hypothesis. It focuses on how these constructions represent state changes, exploring distinctions...This study examines the “V + Dào” construction as a state change event through the lens of the Event Integration Hypothesis. It focuses on how these constructions represent state changes, exploring distinctions between “change” and “stasis”. Using a corpus-based approach, the analysis covers the semantic and syntactic features of “V + Dào” constructions and their event integration patterns. The findings highlight the distribution of agency, animacy, and support relations in state change events, emphasizing the complex interaction of internal and external event integrations and their correlation with the conceptual primitives of change and transition. This study offers insights into the lexicalization and grammaticalization processes of the “V + Dào” construction, and potentially the broader verb-complement constructions in Mandarin.展开更多
Semi-supervised new intent discovery is a significant research focus in natural language understanding.To address the limitations of current semi-supervised training data and the underutilization of implicit informati...Semi-supervised new intent discovery is a significant research focus in natural language understanding.To address the limitations of current semi-supervised training data and the underutilization of implicit information,a Semi-supervised New Intent Discovery for Elastic Neighborhood Syntactic Elimination and Fusion model(SNID-ENSEF)is proposed.Syntactic elimination contrast learning leverages verb-dominant syntactic features,systematically replacing specific words to enhance data diversity.The radius of the positive sample neighborhood is elastically adjusted to eliminate invalid samples and improve training efficiency.A neighborhood sample fusion strategy,based on sample distribution patterns,dynamically adjusts neighborhood size and fuses sample vectors to reduce noise and improve implicit information utilization and discovery accuracy.Experimental results show that SNID-ENSEF achieves average improvements of 0.88%,1.27%,and 1.30%in Normalized Mutual Information(NMI),Accuracy(ACC),and Adjusted Rand Index(ARI),respectively,outperforming PTJN,DPN,MTP-CLNN,and DWG models on the Banking77,StackOverflow,and Clinc150 datasets.The code is available at https://github.com/qsdesz/SNID-ENSEF,accessed on 16 January 2025.展开更多
Grooming,as an evolutionarily conserved repetitive behavior,is common in various animals,including humans,and serves essential functions including,but not limited to,hygiene maintenance,thermoregulation,de-arousal,str...Grooming,as an evolutionarily conserved repetitive behavior,is common in various animals,including humans,and serves essential functions including,but not limited to,hygiene maintenance,thermoregulation,de-arousal,stress reduction,and social behaviors.In rodents,grooming involves a patterned and sequenced structure,known as the syntactic chain with four phases that comprise repeated stereotyped movements happening in a cephalocaudal progression style,beginning from the nose to the face,to the head,and finally ending with body licking.The context-dependent occurrence of grooming behavior indicates its adaptive significance.This review briefly summarizes the neural substrates responsible for rodent grooming behavior and explores its relevance in rodent models of neuropsychiatric disorders and neurodegenerative diseases with aberrant grooming phenotypes.We further emphasize the utility of rodent grooming as a reliable measure of repetitive behavior in neuropsychiatric models,holding promise for translational psychiatry.Herein,we mainly focus on rodent self-grooming.Allogrooming(grooming being applied on one animal by its conspecifics via licking or carefully nibbling)and heterogrooming(a form of grooming behavior directing towards another animal,which occurs in other contexts,such as maternal,sexual,aggressive,or social behaviors)are not covered due to space constraints.展开更多
In recent years,deep learning methods have developed rapidly and found application in many fields,including natural language processing.In the field of aspect-level sentiment analysis,deep learning methods can also gr...In recent years,deep learning methods have developed rapidly and found application in many fields,including natural language processing.In the field of aspect-level sentiment analysis,deep learning methods can also greatly improve the performance of models.However,previous studies did not take into account the relationship between user feature extraction and contextual terms.To address this issue,we use data feature extraction and deep learning combined to develop an aspect-level sentiment analysis method.To be specific,we design user comment feature extraction(UCFE)to distill salient features from users’historical comments and transform them into representative user feature vectors.Then,the aspect-sentence graph convolutional neural network(ASGCN)is used to incorporate innovative techniques for calculating adjacency matrices;meanwhile,ASGCN emphasizes capturing nuanced semantics within relationships among aspect words and syntactic dependency types.Afterward,three embedding methods are devised to embed the user feature vector into the ASGCN model.The empirical validations verify the effectiveness of these models,consistently surpassing conventional benchmarks and reaffirming the indispensable role of deep learning in advancing sentiment analysis methodologies.展开更多
Assembly process documents record the designers'intention or knowledge.However,common knowl-edge extraction methods are not well suitable for assembly process documents,because of its tabular form and unstructured...Assembly process documents record the designers'intention or knowledge.However,common knowl-edge extraction methods are not well suitable for assembly process documents,because of its tabular form and unstructured natural language texts.In this paper,an assembly semantic entity recognition and relation con-struction method oriented to assembly process documents is proposed.First,the assembly process sentences are extracted from the table through concerned region recognition and cell division,and they will be stored as a key-value object file.Then,the semantic entities in the sentence are identified through the sequence tagging model based on the specific attention mechanism for assembly operation type.The syntactic rules are designed for realizing automatic construction of relation between entities.Finally,by using the self-constructed corpus,it is proved that the sequence tagging model in the proposed method performs better than the mainstream named entity recognition model when handling assembly process design language.The effectiveness of the proposed method is also analyzed through the simulation experiment in the small-scale real scene,compared with manual method.The results show that the proposed method can help designers accumulate knowledge automatically and efficiently.展开更多
Nowadays,collaborative writing has gained much attention of many scholars.And task complexity is a crucial factor that influences second language(L2)writing.However,little research has explored how task complexity aff...Nowadays,collaborative writing has gained much attention of many scholars.And task complexity is a crucial factor that influences second language(L2)writing.However,little research has explored how task complexity affects the quality of L2 collaborative writing.This study investigates the impact of task complexity on syntactic complexity,lexical complexity,and accuracy of the second language collaborative writing.English learners(N=50)in a Chinese university were required to complete two writing tasks collaboratively:a simple task and a complex task.Through analyzing their compositions,we found that task complexity has a significant impact on syntactic complexity and high complexity writing tasks help increase the syntactic complexity of second language collaborative writing.However,task complexity has little impact on lexical complexity and accuracy.The accuracy of writing tasks is largely influenced by the task requirements.The research results may enhance the understanding of collaborative writing and task complexity and provide valuable guidance for the second language teaching.展开更多
This study examines the role of the syntactic complexity of the text in the reading comprehension skills of students.Utilizing the qualitative method of research,this paper used structured interview questions as the m...This study examines the role of the syntactic complexity of the text in the reading comprehension skills of students.Utilizing the qualitative method of research,this paper used structured interview questions as the main data-gathering instruments.English language teachers from Coral na Munti National High School were selected as the respondents of the study.Finding of the study suggests that the syntactic complexity of the text affects the reading comprehension of the students.Students found it challenging to understand the message that the author conveyed if he or she used a large number of phrases and clauses in one sentence.Furthermore,the complex sentence syntactic structure was deemed the most challenging for students to understand.To overcome said challenges in comprehending text,various reading intervention programs were utilized by teachers.These interventions include focused or targeted instruction and the implementation of the Project Dear,suggested by the Department of Education.These programs were proven to help students improve their comprehension as well as their knowledge in syntactical structure of sentences.This study underscores the importance of selecting appropriate reading materials and implementing suitable reading intervention programs to enhance students’comprehension skills.展开更多
The rhetorical structure of abstracts has been a widely discussed topic, as it can greatly enhance the abstract writing skills of second-language writers. This study aims to provide guidance on the syntactic features ...The rhetorical structure of abstracts has been a widely discussed topic, as it can greatly enhance the abstract writing skills of second-language writers. This study aims to provide guidance on the syntactic features that L2 learners can employ, as well as suggest which features they should focus on in English academic writing. To achieve this, all samples were analyzed for rhetorical moves using Hyland’s five-rhetorical move model. Additionally, all sentences were evaluated for syntactic complexity, considering measures such as global, clausal and phrasal complexity. The findings reveal that expert writers exhibit a more balanced use of syntactic complexity across moves, effectively fulfilling the rhetorical objectives of abstracts. On the other hand, MA students tend to rely excessively on embedded structures and dependent clauses in an attempt to increase complexity. The implications of these findings for academic writing research, pedagogy, and assessment are thoroughly discussed.展开更多
Aiming at the problem that existing models in aspect-level sentiment analysis cannot fully and effectively utilize sentence semantic and syntactic structure information, this paper proposes a graph neural network-base...Aiming at the problem that existing models in aspect-level sentiment analysis cannot fully and effectively utilize sentence semantic and syntactic structure information, this paper proposes a graph neural network-based aspect-level sentiment classification model. Self-attention, aspectual word multi-head attention and dependent syntactic relations are fused and the node representations are enhanced with graph convolutional networks to enable the model to fully learn the global semantic and syntactic structural information of sentences. Experimental results show that the model performs well on three public benchmark datasets Rest14, Lap14, and Twitter, improving the accuracy of sentiment classification.展开更多
Ambiguity is a unique linguistic feature and is caused by many factors. This paper first introduces the definitions of ambiguity and then mainly illustrates ambiguity in our daily language usage in both English and Ch...Ambiguity is a unique linguistic feature and is caused by many factors. This paper first introduces the definitions of ambiguity and then mainly illustrates ambiguity in our daily language usage in both English and Chinese from phonetic level and syntactic level. People can learn the relationships among those levels and grasp the rule of learning language. Thus, people can realize the complexity and importance of using language and know that it is not easy to express ideas accurately.展开更多
Vagueness is a natural character of language. Vagueness of journalistic English exists in lexical level and syntactic level as well. Lexical vagueness in journalistic English is usually resulted from the indefinite me...Vagueness is a natural character of language. Vagueness of journalistic English exists in lexical level and syntactic level as well. Lexical vagueness in journalistic English is usually resulted from the indefinite meaning of words, while in syntactic level, it may be resulted from the combined use of vague words or the employment of some sentence patterns. This thesis aims to help readers to understand journalistic English from the perspective of vague language.展开更多
The characteristics of authority and standard in Legal English decide the significance of the translation about legal English texts. This thesis presents the stylistic features of legal English. It is hoped that trans...The characteristics of authority and standard in Legal English decide the significance of the translation about legal English texts. This thesis presents the stylistic features of legal English. It is hoped that translators would be able to understand legal English accurately.展开更多
Blog, a new genre of internet communication, has its own unique syntactic features. With Halliday's stylistic analytical pattern, the writer analyzed the samples from the perspectives of linguistic description to ...Blog, a new genre of internet communication, has its own unique syntactic features. With Halliday's stylistic analytical pattern, the writer analyzed the samples from the perspectives of linguistic description to reveal the sentence patterns used in the journal blogs. The results show that blog language displays many of the properties of both spoken and written language.展开更多
This thesis sets out to classify the fossilized errors made by the subjects from lexical and syntactic levels respectively,through the empirical experiment and questionnaire.
It studies William Blake’s poem The Tyger on a basis of the theories of modern stylistics and discusses the meaning realization of the poem from the phonological features, the lexical and syntactic features, and the ...It studies William Blake’s poem The Tyger on a basis of the theories of modern stylistics and discusses the meaning realization of the poem from the phonological features, the lexical and syntactic features, and the semantic features.展开更多
This paper presents a unique and formal method of quantifying the similarity or distance between sedimentary facies successions from measured sections in outcrop or drilled wells and demonstrates its first application...This paper presents a unique and formal method of quantifying the similarity or distance between sedimentary facies successions from measured sections in outcrop or drilled wells and demonstrates its first application in inverse stratigraphic modeling. A sedimentary facies succession is represented with a string of symbols, or facies codes in its natural vertical order, in which each symbol brings with it one attribute such as thickness for the facies. These strings are called attributed strings. A similarity measure is defined between the attributed strings based on a syntactic pattern-recognition technique. A dynamic programming algorithm is used to calculate the similarity. Inverse stratigraphic modeling aims to generate quantitative 3D facies models based on forward stratigraphic modeling that honors observed datasets. One of the key techniques in inverse stratigraphic modeling is how to quantify the similarity or distance between simulated and observed sedimentary facies successions at data locations in order for the forward model to condition the simulation results to the observed dataset such as measured sections or drilled wells. This quantification technique comparing sedimentary successions is demonstrated in the form of a cost function based on the defined distance in our inverse stratigraphic modeling implemented with forward modeling optimization.展开更多
This study investigated how the mode in which the reading-writing integrated continuation task was conducted modulates the effects of second language(L2) syntactic alignment, through the English motion event construct...This study investigated how the mode in which the reading-writing integrated continuation task was conducted modulates the effects of second language(L2) syntactic alignment, through the English motion event construction with manner verbs. Ninety Chinese students were assigned to either of the two experimental groups or a control group, and they all experienced a pretest, an alignment phase and a posttest. In the alignment phase, the two experimental groups completed a reading-writing integrated continuation task but in different modes. For the multi-turn mode,participants reconstructed a picture story by continuing the episodes extracted from the story with one episode presented and continued at a time;for the single-turn mode, the first half of the same picture story was presented as a chunk, and then participants read and continued it. Results show that L2 learners aligned with the target structure in completing the story, and the alignment effect was retained in the posttest conducted after a delay of two weeks. Moreover, syntactic alignment was modulated by task mode with the multi-turn group exhibiting stronger immediate and longterm alignment effects. We conclude that the continuation task is a fruitful context for L2 structural alignment, and the magnitude of alignment effect hinges on interactive intensity.展开更多
基金Sichuan Provincial Science and Technology Support Program,Grant/Award Number:2023YFG0151National Natural Science Foundation of China,Grant/Award Numbers:U22B2061,U2336204。
文摘Existing Chinese named entity recognition(NER)research utilises 1D lexicon-based sequence labelling frameworks,which can only recognise flat entities.While lexicons serve as prior knowledge and enhance semantic information,they also pose completeness and resource requirements limitations.This paper proposes a template-based classification(TC)model to avoid lexicon issues and to identify nested entities.Template-based classification provides a template word for each entity type,which utilises contrastive learning to integrate the common characteristics among entities with the same category.Contrastive learning makes template words the centre points of their category in the vector space,thus improving generalisation ability.Additionally,TC presents a 2D tablefilling label scheme that classifies entities based on the attention distribution of template words.The proposed novel decoder algorithm enables TC recognition of both flat and nested entities simultaneously.Experimental results show that TC achieves the state-ofthe-art performance on five Chinese datasets.
文摘The study employs the theoretical framework of Nanosyntax to analyze the generative mechanism of verbal ABAB reduplication pattern in Mandarin Chinese.The research characterizes ABAB reduplication as an inflectional operation involving functional projections of pluractionality and aspect.It distinguishes between event-internal and event-external pluralization,as well as inner and outer aspect in verbal reduplication.Following the One-Function-One-Head Principle in Nanosyntax,verbal ABAB form occurs through the merging of categoryless roots that are categorized by little v,with the RED affix syncretizing multiple functional morphemes.This framework reduces lexical burden and precisely represents the unique syntactic structure of Chinese verbal reduplication.
文摘This study examines the “V + Dào” construction as a state change event through the lens of the Event Integration Hypothesis. It focuses on how these constructions represent state changes, exploring distinctions between “change” and “stasis”. Using a corpus-based approach, the analysis covers the semantic and syntactic features of “V + Dào” constructions and their event integration patterns. The findings highlight the distribution of agency, animacy, and support relations in state change events, emphasizing the complex interaction of internal and external event integrations and their correlation with the conceptual primitives of change and transition. This study offers insights into the lexicalization and grammaticalization processes of the “V + Dào” construction, and potentially the broader verb-complement constructions in Mandarin.
基金supported by Research Projects of the Nature Science Foundation of Hebei Province(F2021402005).
文摘Semi-supervised new intent discovery is a significant research focus in natural language understanding.To address the limitations of current semi-supervised training data and the underutilization of implicit information,a Semi-supervised New Intent Discovery for Elastic Neighborhood Syntactic Elimination and Fusion model(SNID-ENSEF)is proposed.Syntactic elimination contrast learning leverages verb-dominant syntactic features,systematically replacing specific words to enhance data diversity.The radius of the positive sample neighborhood is elastically adjusted to eliminate invalid samples and improve training efficiency.A neighborhood sample fusion strategy,based on sample distribution patterns,dynamically adjusts neighborhood size and fuses sample vectors to reduce noise and improve implicit information utilization and discovery accuracy.Experimental results show that SNID-ENSEF achieves average improvements of 0.88%,1.27%,and 1.30%in Normalized Mutual Information(NMI),Accuracy(ACC),and Adjusted Rand Index(ARI),respectively,outperforming PTJN,DPN,MTP-CLNN,and DWG models on the Banking77,StackOverflow,and Clinc150 datasets.The code is available at https://github.com/qsdesz/SNID-ENSEF,accessed on 16 January 2025.
基金supported by the National Natural Science Foundation of China(No.82371515)the Talent Initiation BaiRen Plan Start-up Funds(No.E251F811)the State Key Laboratory of Integrated Management of Pest Insects and Rodents(No.IPM2301),China.
文摘Grooming,as an evolutionarily conserved repetitive behavior,is common in various animals,including humans,and serves essential functions including,but not limited to,hygiene maintenance,thermoregulation,de-arousal,stress reduction,and social behaviors.In rodents,grooming involves a patterned and sequenced structure,known as the syntactic chain with four phases that comprise repeated stereotyped movements happening in a cephalocaudal progression style,beginning from the nose to the face,to the head,and finally ending with body licking.The context-dependent occurrence of grooming behavior indicates its adaptive significance.This review briefly summarizes the neural substrates responsible for rodent grooming behavior and explores its relevance in rodent models of neuropsychiatric disorders and neurodegenerative diseases with aberrant grooming phenotypes.We further emphasize the utility of rodent grooming as a reliable measure of repetitive behavior in neuropsychiatric models,holding promise for translational psychiatry.Herein,we mainly focus on rodent self-grooming.Allogrooming(grooming being applied on one animal by its conspecifics via licking or carefully nibbling)and heterogrooming(a form of grooming behavior directing towards another animal,which occurs in other contexts,such as maternal,sexual,aggressive,or social behaviors)are not covered due to space constraints.
基金This work is partly supported by the Fundamental Research Funds for the Central Universities(CUC230A013)It is partly supported by Natural Science Foundation of Beijing Municipality(No.4222038)It is also supported by National Natural Science Foundation of China(Grant No.62176240).
文摘In recent years,deep learning methods have developed rapidly and found application in many fields,including natural language processing.In the field of aspect-level sentiment analysis,deep learning methods can also greatly improve the performance of models.However,previous studies did not take into account the relationship between user feature extraction and contextual terms.To address this issue,we use data feature extraction and deep learning combined to develop an aspect-level sentiment analysis method.To be specific,we design user comment feature extraction(UCFE)to distill salient features from users’historical comments and transform them into representative user feature vectors.Then,the aspect-sentence graph convolutional neural network(ASGCN)is used to incorporate innovative techniques for calculating adjacency matrices;meanwhile,ASGCN emphasizes capturing nuanced semantics within relationships among aspect words and syntactic dependency types.Afterward,three embedding methods are devised to embed the user feature vector into the ASGCN model.The empirical validations verify the effectiveness of these models,consistently surpassing conventional benchmarks and reaffirming the indispensable role of deep learning in advancing sentiment analysis methodologies.
文摘Assembly process documents record the designers'intention or knowledge.However,common knowl-edge extraction methods are not well suitable for assembly process documents,because of its tabular form and unstructured natural language texts.In this paper,an assembly semantic entity recognition and relation con-struction method oriented to assembly process documents is proposed.First,the assembly process sentences are extracted from the table through concerned region recognition and cell division,and they will be stored as a key-value object file.Then,the semantic entities in the sentence are identified through the sequence tagging model based on the specific attention mechanism for assembly operation type.The syntactic rules are designed for realizing automatic construction of relation between entities.Finally,by using the self-constructed corpus,it is proved that the sequence tagging model in the proposed method performs better than the mainstream named entity recognition model when handling assembly process design language.The effectiveness of the proposed method is also analyzed through the simulation experiment in the small-scale real scene,compared with manual method.The results show that the proposed method can help designers accumulate knowledge automatically and efficiently.
文摘Nowadays,collaborative writing has gained much attention of many scholars.And task complexity is a crucial factor that influences second language(L2)writing.However,little research has explored how task complexity affects the quality of L2 collaborative writing.This study investigates the impact of task complexity on syntactic complexity,lexical complexity,and accuracy of the second language collaborative writing.English learners(N=50)in a Chinese university were required to complete two writing tasks collaboratively:a simple task and a complex task.Through analyzing their compositions,we found that task complexity has a significant impact on syntactic complexity and high complexity writing tasks help increase the syntactic complexity of second language collaborative writing.However,task complexity has little impact on lexical complexity and accuracy.The accuracy of writing tasks is largely influenced by the task requirements.The research results may enhance the understanding of collaborative writing and task complexity and provide valuable guidance for the second language teaching.
文摘This study examines the role of the syntactic complexity of the text in the reading comprehension skills of students.Utilizing the qualitative method of research,this paper used structured interview questions as the main data-gathering instruments.English language teachers from Coral na Munti National High School were selected as the respondents of the study.Finding of the study suggests that the syntactic complexity of the text affects the reading comprehension of the students.Students found it challenging to understand the message that the author conveyed if he or she used a large number of phrases and clauses in one sentence.Furthermore,the complex sentence syntactic structure was deemed the most challenging for students to understand.To overcome said challenges in comprehending text,various reading intervention programs were utilized by teachers.These interventions include focused or targeted instruction and the implementation of the Project Dear,suggested by the Department of Education.These programs were proven to help students improve their comprehension as well as their knowledge in syntactical structure of sentences.This study underscores the importance of selecting appropriate reading materials and implementing suitable reading intervention programs to enhance students’comprehension skills.
文摘The rhetorical structure of abstracts has been a widely discussed topic, as it can greatly enhance the abstract writing skills of second-language writers. This study aims to provide guidance on the syntactic features that L2 learners can employ, as well as suggest which features they should focus on in English academic writing. To achieve this, all samples were analyzed for rhetorical moves using Hyland’s five-rhetorical move model. Additionally, all sentences were evaluated for syntactic complexity, considering measures such as global, clausal and phrasal complexity. The findings reveal that expert writers exhibit a more balanced use of syntactic complexity across moves, effectively fulfilling the rhetorical objectives of abstracts. On the other hand, MA students tend to rely excessively on embedded structures and dependent clauses in an attempt to increase complexity. The implications of these findings for academic writing research, pedagogy, and assessment are thoroughly discussed.
文摘Aiming at the problem that existing models in aspect-level sentiment analysis cannot fully and effectively utilize sentence semantic and syntactic structure information, this paper proposes a graph neural network-based aspect-level sentiment classification model. Self-attention, aspectual word multi-head attention and dependent syntactic relations are fused and the node representations are enhanced with graph convolutional networks to enable the model to fully learn the global semantic and syntactic structural information of sentences. Experimental results show that the model performs well on three public benchmark datasets Rest14, Lap14, and Twitter, improving the accuracy of sentiment classification.
文摘Ambiguity is a unique linguistic feature and is caused by many factors. This paper first introduces the definitions of ambiguity and then mainly illustrates ambiguity in our daily language usage in both English and Chinese from phonetic level and syntactic level. People can learn the relationships among those levels and grasp the rule of learning language. Thus, people can realize the complexity and importance of using language and know that it is not easy to express ideas accurately.
文摘Vagueness is a natural character of language. Vagueness of journalistic English exists in lexical level and syntactic level as well. Lexical vagueness in journalistic English is usually resulted from the indefinite meaning of words, while in syntactic level, it may be resulted from the combined use of vague words or the employment of some sentence patterns. This thesis aims to help readers to understand journalistic English from the perspective of vague language.
文摘The characteristics of authority and standard in Legal English decide the significance of the translation about legal English texts. This thesis presents the stylistic features of legal English. It is hoped that translators would be able to understand legal English accurately.
文摘Blog, a new genre of internet communication, has its own unique syntactic features. With Halliday's stylistic analytical pattern, the writer analyzed the samples from the perspectives of linguistic description to reveal the sentence patterns used in the journal blogs. The results show that blog language displays many of the properties of both spoken and written language.
文摘This thesis sets out to classify the fossilized errors made by the subjects from lexical and syntactic levels respectively,through the empirical experiment and questionnaire.
文摘It studies William Blake’s poem The Tyger on a basis of the theories of modern stylistics and discusses the meaning realization of the poem from the phonological features, the lexical and syntactic features, and the semantic features.
基金financially was supported by Colorado School of Minessupported by the Science and Technology Ministry of China (2016ZX05033003)+1 种基金China Academy of Sciences (XDA14010204)Sinopec (G5800-15-ZS-KJB016)
文摘This paper presents a unique and formal method of quantifying the similarity or distance between sedimentary facies successions from measured sections in outcrop or drilled wells and demonstrates its first application in inverse stratigraphic modeling. A sedimentary facies succession is represented with a string of symbols, or facies codes in its natural vertical order, in which each symbol brings with it one attribute such as thickness for the facies. These strings are called attributed strings. A similarity measure is defined between the attributed strings based on a syntactic pattern-recognition technique. A dynamic programming algorithm is used to calculate the similarity. Inverse stratigraphic modeling aims to generate quantitative 3D facies models based on forward stratigraphic modeling that honors observed datasets. One of the key techniques in inverse stratigraphic modeling is how to quantify the similarity or distance between simulated and observed sedimentary facies successions at data locations in order for the forward model to condition the simulation results to the observed dataset such as measured sections or drilled wells. This quantification technique comparing sedimentary successions is demonstrated in the form of a cost function based on the defined distance in our inverse stratigraphic modeling implemented with forward modeling optimization.
文摘This study investigated how the mode in which the reading-writing integrated continuation task was conducted modulates the effects of second language(L2) syntactic alignment, through the English motion event construction with manner verbs. Ninety Chinese students were assigned to either of the two experimental groups or a control group, and they all experienced a pretest, an alignment phase and a posttest. In the alignment phase, the two experimental groups completed a reading-writing integrated continuation task but in different modes. For the multi-turn mode,participants reconstructed a picture story by continuing the episodes extracted from the story with one episode presented and continued at a time;for the single-turn mode, the first half of the same picture story was presented as a chunk, and then participants read and continued it. Results show that L2 learners aligned with the target structure in completing the story, and the alignment effect was retained in the posttest conducted after a delay of two weeks. Moreover, syntactic alignment was modulated by task mode with the multi-turn group exhibiting stronger immediate and longterm alignment effects. We conclude that the continuation task is a fruitful context for L2 structural alignment, and the magnitude of alignment effect hinges on interactive intensity.
