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Syntactic word embedding based on dependency syntax and polysemous analysis None

Zhong-lin YE, Hai-xing ZHAO

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 4,   Pages 524-535 doi: 10.1631/FITEE.1601846

Abstract: Most word embedding models have the following problems: (1) In the models based on bag-of-words contexts, the structural relations of sentences are completely neglected; (2) Each word uses a single embedding, which makes the model indiscriminative for polysemous words; (3) Word embedding easily tends to contextualTo solve these problems, we propose an easy-to-use representation algorithm of syntactic word embeddingThe main procedures are: (1) A polysemous tagging algorithm is used for polysemous representation by

Keywords： Dependency-based context     Polysemous word representation     Representation learning     Syntactic word embedding    

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Corpus-based research on English word recognition rates in primary school and word selection strategy Article

Wen-yan XIAO,Ming-wen WANG,Zhen WENG,Li-lin ZHANG,Jia-li ZUO

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 3,   Pages 362-372 doi: 10.1631/FITEE.1601118

Abstract: In this paper, we develop an English webpage corpus (EWC) and create a word frequency list using webBy comparing EWC word lists with the British National Corpus (BNC), we find that the BNC word frequencyWe also explore primary school students’ English word recognition rates by comparing the word frequencyThe results show that the word recognition rates for primary school children are relatively low in bothMotivated by the experiment results, we finally propose some word-selection strategies for compiling

Keywords： Corpus     Primary English     Recognition rate     Word frequency     Coverage rate    

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interpretation of textbook vocabulary lists: comments on Xiao et al.’s Corpus-based research on English wordrecognition rates in primary school and word selection strategy Correspondence

Qiong HU, Ming YUE

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 7,   Pages 863-866 doi: 10.1631/FITEE.1700418

Abstract: Xiao et al. (2017)在对比分析4个语料库的基础上，提出国内小学六年级学生的识词率增长不能令人满意的观点，建议人教版小学英语通用教材总词汇在原有726个的基础上再增加903个，并删除twelfth（序数词，第十二）这样的低频词。作为外语教师和语言学家，我们赞同他们应用先进信息技术对传统词表进行评估的做法，但认为这项工作：1. 在构建参考语料库时需重视语料抽样的合理性；2. 在解读词频时需重视齐夫定律（Zipf’s law，即英语词频与词秩成反比）的作用——识字率增长随词汇量增加而减缓的情况是合理的；3. 在提出教材选词策略时，需考虑小学生认知特点和课业负担等现实因素限制，以及语言教育的总体目标，不能随便删除twelfth这样承载文化的词汇；4. 学龄儿童全国通用外语教材编写是项复杂的系统工程，需要各领域专家共同关注。

Keywords： 齐夫定律（Zipf’s law）；语料库；英语；教科书；词表    

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Standard model of knowledge representation

Wensheng YIN

Frontiers of Mechanical Engineering 2016, Volume 11, Issue 3,   Pages 275-288 doi: 10.1007/s11465-016-0372-3

Abstract:

Knowledge representation is the core of artificial intelligence research.Knowledge representation methods include predicate logic, semantic network, computer programming languageTo establish the intrinsic link between various knowledge representation methods, a unified knowledgerepresentation model is necessary.This knowledge representation method is not a contradiction to the traditional knowledge representation

Keywords： knowledge representation     standard model     ontology     system theory     control theory     multidimensional representation    

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Performance analysis of new word weighting procedures for opinion mining Article

G. R. BRINDHA,P. SWAMINATHAN,B. SANTHI

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 11,   Pages 1186-1198 doi: 10.1631/FITEE.1500283

Abstract: and to enhance opinion mining analysis, we propose a novel weighting scheme, referred to as inferred wordIWW is computed based on the significance of the word in the document (SWD) and the significance of theword in the expression (SWE) to enhance their performance.

Keywords： Inferred word weight     Opinion mining     Supervised classification     Support vector machine (SVM)     Machine    

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Applicability of high dimensional model representation correlations for ignition delay times of n-heptane

Wang LIU, Jiabo ZHANG, Zhen HUANG, Dong HAN

Frontiers in Energy 2019, Volume 13, Issue 2,   Pages 367-376 doi: 10.1007/s11708-018-0584-9

Abstract: In this paper, the random sampling-high dimensional model representation (RS-HDMR) methods were employed

Keywords： ignition delay     random sampling     high dimensional model representation     n-heptane     fuel kinetics    

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Digital representation of meso-geomaterial spatial distribution and associated numerical analysis of

YUE Zhongqi

Frontiers of Structural and Civil Engineering 2007, Volume 1, Issue 1,   Pages 80-93 doi: 10.1007/s11709-007-0008-0

Abstract: presents the author's efforts in the past decade for the establishment of a practical approach of digital representationproposed approach, digital image processing methods are used as measurement tools to construct a digital representation

Keywords： homogeneous     numerical analysis     Expanded     homogenization     meso-level    

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Uncertainty in Knowledge Representation

Li Deyi

Strategic Study of CAE 2000, Volume 2, Issue 10,   Pages 73-79

Abstract:

Knowledge representation in AI has been a bottleneck for years.

Keywords： knowledge representation     qualitative concept     uncertainty     cloud model     digital characteristics    

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A discussion of objective function representation methods in global optimization

Panos M. PARDALOS, Mahdi FATHI

Frontiers of Engineering Management 2018, Volume 5, Issue 4,   Pages 515-523 doi: 10.15302/J-FEM-2018044

Abstract: We examine decomposition techniques and classify GO problems on the basis of objective function representationFinally, we conclude the paper by exploring the importance of objective function representation in integrated

Keywords： global optimization     decomposition techniques     multi-objective     DC programming     Kolmogorov’s superposition     space-filling curve     smart manufacturing and Industry 4.0    

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Multiple Knowledge Representation of Artificial Intelligence

Yunhe Pan

Engineering 2020, Volume 6, Issue 3,   Pages 216-217 doi: 10.1016/j.eng.2019.12.011

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Sharpest Contradiction and Most Favourable Opportunity ——A word on development of Chinese architectural

Wu Liangyong

Strategic Study of CAE 2004, Volume 6, Issue 2,   Pages 13-16

Abstract:

With the urbanization in China entering the period of accelerated development, the flourish of building industry has attracted numerous foreign architects offices to come to China for “seizing a beach before others”.The crisis for Chinese construction industry companies lies in the fact that they usually can not take charge of important projects but only act as secondaries or cooperators; urban planning and architectural design are not supported by comprehensive scientific demonstration and some big cities become test sites for freakish architectural designs of foreign architects; residential environment is not stressed on, economics and practicability is not given importance but instead peculiarity and novelty is one-sidedly sought for. This paper emphatically points out that architectural buildings and urban planning are closely related to the function, economy, technology, environment, etc. of a city, being an open macroscopic system of the city. Hence basic principles of architecture should be followed, more architectural factors should be considered so that architecture, landscape and urban planning are merged into a homogenous entirety. While the trend of globalization is tracked, more important is the inheritance and innovation of local and traditional culture. The academic level of a modern architect can only be based on his rich cultural background, trans-science learning and solid speciality knowledge.

Keywords： urbanization     architecture science     development opportunity for Chinese architecture    

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Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and unary classification

Frontiers in Energy 2023, Volume 17, Issue 4,   Pages 527-544 doi: 10.1007/s11708-023-0880-x

Abstract: The self-supervised representation learning uses a sequence-based Triplet Loss.

Keywords： fault detection     unary classification     self-supervised representation learning     multivariate nonlinear    

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Development of an artificial intelligence diagnostic model based on dynamic uncertain causality graph for the differential diagnosis of dyspnea

Yang Jiao, Zhan Zhang, Ting Zhang, Wen Shi, Yan Zhu, Jie Hu, Qin Zhang

Frontiers of Medicine 2020, Volume 14, Issue 4,   Pages 488-497 doi: 10.1007/s11684-020-0762-0

Abstract: Dyspnea is one of the most common manifestations of patients with pulmonary disease, myocardial dysfunction, and neuromuscular disorder, among other conditions. Identifying the causes of dyspnea in clinical practice, especially for the general practitioner, remains a challenge. This pilot study aimed to develop a computer-aided tool for improving the efficiency of differential diagnosis. The disease set with dyspnea as the chief complaint was established on the basis of clinical experience and epidemiological data. Differential diagnosis approaches were established and optimized by clinical experts. The artificial intelligence (AI) diagnosis model was constructed according to the dynamic uncertain causality graph knowledge-based editor. Twenty-eight diseases and syndromes were included in the disease set. The model contained 132 variables of symptoms, signs, and serological and imaging parameters. Medical records from the electronic hospital records of Suining Central Hospital were randomly selected. A total of 202 discharged patients with dyspnea as the chief complaint were included for verification, in which the diagnoses of 195 cases were coincident with the record certified as correct. The overall diagnostic accuracy rate of the model was 96.5%. In conclusion, the diagnostic accuracy of the AI model is promising and may compensate for the limitation of medical experience.

Keywords： knowledge representation     uncertain     causality     graphical model     artificial intelligence     diagnosis     dyspnea    

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Symbolic representation based on trend features for knowledge discovery in long time series

Hong YIN,Shu-qiang YANG,Xiao-qian ZHU,Shao-dong MA,Lu-min ZHANG

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 9,   Pages 744-758 doi: 10.1631/FITEE.1400376

Abstract: The symbolic representation of time series has attracted much research interest recently.In this paper, we propose a new symbolic representation method for long time series based on trend features

Keywords： Long time series     Segmentation     Trend features     Symbolic     Knowledge discovery    

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The brain areas and the neural mechanism involved in the Chinese paired-word associated learning and

Zheng Jinlong,Shu Siyun,Liu Songhao,Guo Zhouyi,Wu Yongming,Bao Xinmin,Zhang Zengqiang,Jin Mei,Ma Hanzhang

Strategic Study of CAE 2008, Volume 10, Issue 5,   Pages 38-45

Abstract: This paper is to investigate the activated brain areas and the neuronal mechanism of Chinese paired-wordresonance imaging (fMRI) technique. 16 right-handed normal volunteers participated in a test of paired-wordwas used to analyze the data and to get the activated brain regions. 14 volunteers passed the paired-wordlobe were more activative than others in scope and brightness during the coding stage of the paired-wordThe MrD of the striatum was mainly involved in coding stages of the paired-word associated learning and

Keywords： functional magnetic resonance imaging (fMRI) of human brain     paired-word     language     associated learning    

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Title Author Date Type Operation

Syntactic word embedding based on dependency syntax and polysemous analysis

Zhong-lin YE, Hai-xing ZHAO

Journal Article

Corpus-based research on English word recognition rates in primary school and word selection strategy

Wen-yan XIAO,Ming-wen WANG,Zhen WENG,Li-lin ZHANG,Jia-li ZUO

Journal Article

interpretation of textbook vocabulary lists: comments on Xiao et al.’s Corpus-based research on English wordrecognition rates in primary school and word selection strategy

Qiong HU, Ming YUE

Journal Article

Standard model of knowledge representation

Wensheng YIN

Journal Article

Performance analysis of new word weighting procedures for opinion mining

G. R. BRINDHA,P. SWAMINATHAN,B. SANTHI

Journal Article

Applicability of high dimensional model representation correlations for ignition delay times of n-heptane

Wang LIU, Jiabo ZHANG, Zhen HUANG, Dong HAN

Journal Article

Digital representation of meso-geomaterial spatial distribution and associated numerical analysis of

YUE Zhongqi

Journal Article

Uncertainty in Knowledge Representation

Li Deyi

Journal Article

A discussion of objective function representation methods in global optimization

Panos M. PARDALOS, Mahdi FATHI

Journal Article

Multiple Knowledge Representation of Artificial Intelligence

Yunhe Pan

Journal Article

Sharpest Contradiction and Most Favourable Opportunity ——A word on development of Chinese architectural

Wu Liangyong

Journal Article

Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and unary classification

Journal Article

Development of an artificial intelligence diagnostic model based on dynamic uncertain causality graph for the differential diagnosis of dyspnea

Yang Jiao, Zhan Zhang, Ting Zhang, Wen Shi, Yan Zhu, Jie Hu, Qin Zhang

Journal Article

Symbolic representation based on trend features for knowledge discovery in long time series

Hong YIN,Shu-qiang YANG,Xiao-qian ZHU,Shao-dong MA,Lu-min ZHANG

Journal Article

The brain areas and the neural mechanism involved in the Chinese paired-word associated learning and

Zheng Jinlong,Shu Siyun,Liu Songhao,Guo Zhouyi,Wu Yongming,Bao Xinmin,Zhang Zengqiang,Jin Mei,Ma Hanzhang

Journal Article