Purpose:To uncover the evaluation information on the academic contribution of research papers cited by peers based on the content cited by citing papers,and to provide an evidencebased tool for evaluating the academic...Purpose:To uncover the evaluation information on the academic contribution of research papers cited by peers based on the content cited by citing papers,and to provide an evidencebased tool for evaluating the academic value of cited papers.Design/methodology/approach:CiteOpinion uses a deep learning model to automatically extract citing sentences from representative citing papers;it starts with an analysis on the citing sentences,then it identifies major academic contribution points of the cited paper,positive/negative evaluations from citing authors and the changes in the subjects of subsequent citing authors by means of Recognizing Categories of Moves(problems,methods,conclusions,etc.),and sentiment analysis and topic clustering.Findings:Citing sentences in a citing paper contain substantial evidences useful for academic evaluation.They can also be used to objectively and authentically reveal the nature and degree of contribution of the cited paper reflected by citation,beyond simple citation statistics.Practical implications:The evidence-based evaluation tool CiteOpinion can provide an objective and in-depth academic value evaluation basis for the representative papers of scientific researchers,research teams,and institutions.Originality/value:No other similar practical tool is found in papers retrieved.Research limitations:There are difficulties in acquiring full text of citing papers.There is a need to refine the calculation based on the sentiment scores of citing sentences.Currently,the tool is only used for academic contribution evaluation,while its value in policy studies,technical application,and promotion of science is not yet tested.展开更多
In order to convey complete meanings,there is a phenomenon in Chinese of using multiple running sentences.Xu Jingning(2023,p.66)states,“In communication,a complete expression of meaning often requires more than one c...In order to convey complete meanings,there is a phenomenon in Chinese of using multiple running sentences.Xu Jingning(2023,p.66)states,“In communication,a complete expression of meaning often requires more than one clause,which is common in human languages.”Domestic research on running sentences includes discussions on defining the concept and structural features of running sentences,sentence properties,sentence pattern classifications and their criteria,as well as issues related to translating running sentences into English.This article primarily focuses on scholarly research into the English translation of running sentences in China,highlighting recent achievements and identifying existing issues in the study of running sentence translation.However,by reviewing literature on the translation of running sentences,it is found that current research in the academic community on non-core running sentences is limited.Therefore,this paper proposes relevant strategies to address this issue.展开更多
This paper intends to analyze the six types of English imperative sentences proposed by Chen (1984) from a perspective of causal-chain windowing. It comes to the conclusions that Talmy's causal-chain windowing app...This paper intends to analyze the six types of English imperative sentences proposed by Chen (1984) from a perspective of causal-chain windowing. It comes to the conclusions that Talmy's causal-chain windowing approach as well as the cognitive underpinnings of causal windowing and gapping is proved to be applicable in English imperative structures, and that generally speaking, the final portion of an imperative sentence is always windowed while the intermediate portions gapped.展开更多
Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requir...Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requires more syntactic elements.Most existing strategies focus on the general semantics of a conversation without involving the context of the sentence,recognizing the progress and comparing impacts.An ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation corpus.The conversational sentences are classified into four categories:information,question,directive,and commission.These classification label sequences are for analyzing the conversation progress and predicting the pecking order of the conversation.Ensemble of Bidirectional Encoder for Representation of Transformer(BERT),Robustly Optimized BERT pretraining Approach(RoBERTa),Generative Pre-Trained Transformer(GPT),DistilBERT and Generalized Autoregressive Pretraining for Language Understanding(XLNet)models are trained on conversation corpus with hyperparameters.Hyperparameter tuning approach is carried out for better performance on sentence classification.This Ensemble of Pre-trained Language Models with a Hyperparameter Tuning(EPLM-HT)system is trained on an annotated conversation dataset.The proposed approach outperformed compared to the base BERT,GPT,DistilBERT and XLNet transformer models.The proposed ensemble model with the fine-tuned parameters achieved an F1_score of 0.88.展开更多
The Ba sentence is unique existence in Chinese. There is no corresponding sentence pattern in English. Thus, the translation of Ba sentences is a challenge for translators. Even with the myriad analyses on the transla...The Ba sentence is unique existence in Chinese. There is no corresponding sentence pattern in English. Thus, the translation of Ba sentences is a challenge for translators. Even with the myriad analyses on the translation of Ba sentences, small quantity of them demonstrates the correctness and the reading effect of the translation by using a specific theory. And the image schema theory reflects the projects between the source domain and the target domain, while in the translation analysis there are schemata in the source language and the target language. So the paper does comparisons of schemata between the source text and the target text of Ba sentences, which are chosen from the English translation of Words of Fire—Poems by Jidi Majia translated by Denis Mair. After the demonstration, the following conclusions are found: First, the schema of the sentence is decided by verbs of the Ba sentences, rather than by the sentence structures;second, the image schema is a feasible tool to check correctness of Ba sentences translation.展开更多
Of Time and the River is a famous novel written by American novelist–Thomas Wolfe who was a major American novelist of the early 20th century.His books are well received among Chinese readers.In the novel—Of Time an...Of Time and the River is a famous novel written by American novelist–Thomas Wolfe who was a major American novelist of the early 20th century.His books are well received among Chinese readers.In the novel—Of Time and the River,we can find Wolfe’s frequent use of long sentences.In this paper,the skills of translating long sentences and the ways of analyzing sentence structures are discussed by several examples selected from the novel.Based on my own translation,we can find the importance of sentence structure analysis in translating long sentences.展开更多
Based on the paraphrasing of Chinese simple sentences,the complex sentence paraphrasing by using templates are studied.Through the classification of complex sentences,syntactic analysis and structural anal...Based on the paraphrasing of Chinese simple sentences,the complex sentence paraphrasing by using templates are studied.Through the classification of complex sentences,syntactic analysis and structural analysis,the proposed methods construct complex sentence paraphrasing templates that the associated words are as the core.The part of speech tagging is used in the calculation of the similarity between the paraphrasing sentences and the paraphrasing template.The joint complex sentence can be divided into parallel relationship,sequence relationship,selection relationship,progressive relationship,and interpretive relationship’s complex sentences.The subordinate complex sentence can be divided into transition relationship,conditional relationship,hypothesis relationship,causal relationship and objective relationship’s complex sentences.Joint complex sentence and subordinate complex sentence are divided to associated words.By using pretreated sentences,the preliminary experiment is carried out to decide the threshold between the paraphrasing sentence and the template.A small scale paraphrase experiment shows the method is availability,acquire the coverage rate of paraphrasing template 40.20%and the paraphrase correct rate 62.61%.展开更多
Dealing with issues such as too simple image features and word noise inference in product image sentence anmotation, a product image sentence annotation model focusing on image feature learning and key words summariza...Dealing with issues such as too simple image features and word noise inference in product image sentence anmotation, a product image sentence annotation model focusing on image feature learning and key words summarization is described. Three kernel descriptors such as gradient, shape, and color are extracted, respectively. Feature late-fusion is executed in turn by the multiple kernel learning model to obtain more discriminant image features. Absolute rank and relative rank of the tag-rank model are used to boost the key words' weights. A new word integration algorithm named word sequence blocks building (WSBB) is designed to create N-gram word sequences. Sentences are generated according to the N-gram word sequences and predefined templates. Experimental results show that both the BLEU-1 scores and BLEU-2 scores of the sentences are superior to those of the state-of-art baselines.展开更多
文摘Purpose:To uncover the evaluation information on the academic contribution of research papers cited by peers based on the content cited by citing papers,and to provide an evidencebased tool for evaluating the academic value of cited papers.Design/methodology/approach:CiteOpinion uses a deep learning model to automatically extract citing sentences from representative citing papers;it starts with an analysis on the citing sentences,then it identifies major academic contribution points of the cited paper,positive/negative evaluations from citing authors and the changes in the subjects of subsequent citing authors by means of Recognizing Categories of Moves(problems,methods,conclusions,etc.),and sentiment analysis and topic clustering.Findings:Citing sentences in a citing paper contain substantial evidences useful for academic evaluation.They can also be used to objectively and authentically reveal the nature and degree of contribution of the cited paper reflected by citation,beyond simple citation statistics.Practical implications:The evidence-based evaluation tool CiteOpinion can provide an objective and in-depth academic value evaluation basis for the representative papers of scientific researchers,research teams,and institutions.Originality/value:No other similar practical tool is found in papers retrieved.Research limitations:There are difficulties in acquiring full text of citing papers.There is a need to refine the calculation based on the sentiment scores of citing sentences.Currently,the tool is only used for academic contribution evaluation,while its value in policy studies,technical application,and promotion of science is not yet tested.
文摘In order to convey complete meanings,there is a phenomenon in Chinese of using multiple running sentences.Xu Jingning(2023,p.66)states,“In communication,a complete expression of meaning often requires more than one clause,which is common in human languages.”Domestic research on running sentences includes discussions on defining the concept and structural features of running sentences,sentence properties,sentence pattern classifications and their criteria,as well as issues related to translating running sentences into English.This article primarily focuses on scholarly research into the English translation of running sentences in China,highlighting recent achievements and identifying existing issues in the study of running sentence translation.However,by reviewing literature on the translation of running sentences,it is found that current research in the academic community on non-core running sentences is limited.Therefore,this paper proposes relevant strategies to address this issue.
文摘This paper intends to analyze the six types of English imperative sentences proposed by Chen (1984) from a perspective of causal-chain windowing. It comes to the conclusions that Talmy's causal-chain windowing approach as well as the cognitive underpinnings of causal windowing and gapping is proved to be applicable in English imperative structures, and that generally speaking, the final portion of an imperative sentence is always windowed while the intermediate portions gapped.
文摘Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requires more syntactic elements.Most existing strategies focus on the general semantics of a conversation without involving the context of the sentence,recognizing the progress and comparing impacts.An ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation corpus.The conversational sentences are classified into four categories:information,question,directive,and commission.These classification label sequences are for analyzing the conversation progress and predicting the pecking order of the conversation.Ensemble of Bidirectional Encoder for Representation of Transformer(BERT),Robustly Optimized BERT pretraining Approach(RoBERTa),Generative Pre-Trained Transformer(GPT),DistilBERT and Generalized Autoregressive Pretraining for Language Understanding(XLNet)models are trained on conversation corpus with hyperparameters.Hyperparameter tuning approach is carried out for better performance on sentence classification.This Ensemble of Pre-trained Language Models with a Hyperparameter Tuning(EPLM-HT)system is trained on an annotated conversation dataset.The proposed approach outperformed compared to the base BERT,GPT,DistilBERT and XLNet transformer models.The proposed ensemble model with the fine-tuned parameters achieved an F1_score of 0.88.
文摘The Ba sentence is unique existence in Chinese. There is no corresponding sentence pattern in English. Thus, the translation of Ba sentences is a challenge for translators. Even with the myriad analyses on the translation of Ba sentences, small quantity of them demonstrates the correctness and the reading effect of the translation by using a specific theory. And the image schema theory reflects the projects between the source domain and the target domain, while in the translation analysis there are schemata in the source language and the target language. So the paper does comparisons of schemata between the source text and the target text of Ba sentences, which are chosen from the English translation of Words of Fire—Poems by Jidi Majia translated by Denis Mair. After the demonstration, the following conclusions are found: First, the schema of the sentence is decided by verbs of the Ba sentences, rather than by the sentence structures;second, the image schema is a feasible tool to check correctness of Ba sentences translation.
文摘Of Time and the River is a famous novel written by American novelist–Thomas Wolfe who was a major American novelist of the early 20th century.His books are well received among Chinese readers.In the novel—Of Time and the River,we can find Wolfe’s frequent use of long sentences.In this paper,the skills of translating long sentences and the ways of analyzing sentence structures are discussed by several examples selected from the novel.Based on my own translation,we can find the importance of sentence structure analysis in translating long sentences.
文摘Based on the paraphrasing of Chinese simple sentences,the complex sentence paraphrasing by using templates are studied.Through the classification of complex sentences,syntactic analysis and structural analysis,the proposed methods construct complex sentence paraphrasing templates that the associated words are as the core.The part of speech tagging is used in the calculation of the similarity between the paraphrasing sentences and the paraphrasing template.The joint complex sentence can be divided into parallel relationship,sequence relationship,selection relationship,progressive relationship,and interpretive relationship’s complex sentences.The subordinate complex sentence can be divided into transition relationship,conditional relationship,hypothesis relationship,causal relationship and objective relationship’s complex sentences.Joint complex sentence and subordinate complex sentence are divided to associated words.By using pretreated sentences,the preliminary experiment is carried out to decide the threshold between the paraphrasing sentence and the template.A small scale paraphrase experiment shows the method is availability,acquire the coverage rate of paraphrasing template 40.20%and the paraphrase correct rate 62.61%.
基金The National Natural Science Foundation of China(No.61133012)the Humanity and Social Science Foundation of the Ministry of Education(No.12YJCZH274)+1 种基金the Humanity and Social Science Foundation of Jiangxi Province(No.XW1502,TQ1503)the Science and Technology Project of Jiangxi Science and Technology Department(No.20121BBG70050,20142BBG70011)
文摘Dealing with issues such as too simple image features and word noise inference in product image sentence anmotation, a product image sentence annotation model focusing on image feature learning and key words summarization is described. Three kernel descriptors such as gradient, shape, and color are extracted, respectively. Feature late-fusion is executed in turn by the multiple kernel learning model to obtain more discriminant image features. Absolute rank and relative rank of the tag-rank model are used to boost the key words' weights. A new word integration algorithm named word sequence blocks building (WSBB) is designed to create N-gram word sequences. Sentences are generated according to the N-gram word sequences and predefined templates. Experimental results show that both the BLEU-1 scores and BLEU-2 scores of the sentences are superior to those of the state-of-art baselines.