On Associative Meanings of Color-Related English Words from the Perspective of Cognitive Metaphor

As an important metaphor, metaphor of color-related English words regards color domain as source domain, and maps the color domain to non-colored abstract domain. This enables us to understand, think and discuss color-related concept. This paper studies the basic color-related English words through cognitive metaphor. The process of exploring the associative meanings of the color-related English words is in nature to understand the cultural connotation of color-related English words by means of cognitive metaphor under different cultural backgrounds.

Chinese emotional words in patients with major depressive disorder during a subliminal Stroop task An event-related potential study

Patients with major depressive disorder （MDD） develop a negative cognitive bias, but how they respond to information in Chinese emotional words is unclear. Here we used a Stroop paradigm with subliminal Chinese emotional words to explore the event-related potential components of abnormal emotional processing Jn patients with MDD. The correct rate was similar in MDD and normal control groups, but MDD reaction time was longer than the normal controls, especially to the negative and neutral stimuli. In N270, repeated-measure analysis of variance demonstrated a significant main effect of the relation electrode and valence on peak amplitude and interactions between valence and electrode site. The peak amplitudes of the three kinds of words were different in the two groups （positive 〉 negative 〉 neutral）. The topography of the difference waves indicated that the difference distributed in the frontal and left parietal-temporal sites across the scalp. In N400, there was a significant main effect of the relation electrode and valence on peak amplitude, and the latency showed a main effect of the electrode and an interaction between electrode and group. The amplitudes induced by type of words were significantly different from each other in both groups （positive 〉 negative 〉 neutral）. The topography of the difference waves indicated that the effect of relation type was primarily at left and right frontal and central and left parietal-temporal regions. Both MDD patients and normal controls exhibited significant emotional Stroop effects during the processing of positive/negative Chinese emotional words. MDD patients showed interference in emotional stimuli in early cognitive processing that induced psychological resource intervention during late emotional information processing.

How to Deal with New Words in Material——What is a Word and its Relations to the Reading

When you mention lexicology,absolutely it is a branch of linguistics,inquiring into the origins and meanings of words.The lexicologist Mc Carthy(1990)have given us his opinion about it.He said,grammar is important,and it indeed plays a vital rolein English study,but that is not all.In fact,tar from this.From this we can see,vocabulary and the study and learning of vocabularytake an outstanding place in the study of language,it will improve his skills of using reference books and raise his problem-solvingability and efficiency of individual study.And it will make you much more receptive and productive in language processing and lan-guage production.Knowledge of English Lexicology can offer a great help to the work of the teachers of English.Armed with thisknowledge,they can better control the teaching materials,especially the concerning words.They can also select and organize mate-rials to teach in a more effective way.What is more,they can make use of the different sense relations to group vocabulary,inter-pret words and explain meanings to the students;At last,their teaching will prove better if they have the knowledge of dictionaries.In my thesis,I will talk about how to deal with new words in material.

A New Citation Recommendation Strategy Based on Term Functions in Related Studies Section

Purpose:Researchers frequently encounter the following problems when writing scientific articles:(1)Selecting appropriate citations to support the research idea is challenging.(2)The literature review is not conducted extensively,which leads to working on a research problem that others have well addressed.The study focuses on citation recommendation in the related studies section by applying the term function of a citation context,potentially improving the efficiency of writing a literature review.Design/methodology/approach:We present nine term functions with three newly created and six identified from existing literature.Using these term functions as labels,we annotate 531 research papers in three topics to evaluate our proposed recommendation strategy.BM25 and Word2vec with VSM are implemented as the baseline models for the recommendation.Then the term function information is applied to enhance the performance.Findings:The experiments show that the term function-based methods outperform the baseline methods regarding the recall,precision,and F1-score measurement,demonstrating that term functions are useful in identifying valuable citations.Research limitations:The dataset is insufficient due to the complexity of annotating citation functions for paragraphs in the related studies section.More recent deep learning models should be performed to future validate the proposed approach.Practical implications:The citation recommendation strategy can be helpful for valuable citation discovery,semantic scientific retrieval,and automatic literature review generation.Originality/value:The proposed citation function-based citation recommendation can generate intuitive explanations of the results for users,improving the transparency,persuasiveness,and effectiveness of recommender systems.

Solving Arithmetic Word Problems of Entailing Deep Implicit Relations by Qualia Syntax-Semantic Model

Solving arithmetic word problems that entail deep implicit relations is still a challenging problem.However,significant progress has been made in solving Arithmetic Word Problems(AWP)over the past six decades.This paper proposes to discover deep implicit relations by qualia inference to solve Arithmetic Word Problems entailing Deep Implicit Relations(DIR-AWP),such as entailing commonsense or subject-domain knowledge involved in the problem-solving process.This paper proposes to take three steps to solve DIR-AWPs,in which the first three steps are used to conduct the qualia inference process.The first step uses the prepared set of qualia-quantity models to identify qualia scenes from the explicit relations extracted by the Syntax-Semantic(S2)method from the given problem.The second step adds missing entities and deep implicit relations in order using the identified qualia scenes and the qualia-quantity models,respectively.The third step distills the relations for solving the given problem by pruning the spare branches of the qualia dependency graph of all the acquired relations.The research contributes to the field by presenting a comprehensive approach combining explicit and implicit knowledge to enhance reasoning abilities.The experimental results on Math23K demonstrate hat the proposed algorithm is superior to the baseline algorithms in solving AWPs requiring deep implicit relations.

Semantic Features and Applications in Translation of English Words in Pairs

English words in pairs are a special form of English idioms, which have different kinds and are used widely. For English learners, words in pairs are one of the difficult points. This paper discusses their form patterns, semantic relations, grammatical functions, rhetoric features and their application in translation. Its purpose is to help learners understand and use them accurately and correctly so as to improve language expressing ability.

An event-related potential observation of preposition processing in Chinese: Is N280 a specific component for Chinese prepositions?

BACKGROUND： Studies have shown that closed-class words, such as prepositions and conjunctions, induce a left anterior negativity （N280）, indicating that N280 should be a specific component of the word category. OBJECTIVE： To observe if Chinese prepositions and verbs exhibit different linguistic functions, to determine whether they are processed by different neural systems, and to verify that N280 is a specific component. DESIGN, TIME AND SETTING： The observed neurolinguistics experiment was performed at Xuzhou Normal University between November and December 2006. PARTICIPANTS： Sixteen undergraduate students, comprising 8 females and 8 males, with no mental or neuropathological history, were selected. METHODS： A total of 15 verbs and prepositions were used as linguistic stimuli, and each verb and preposition was combined to produce four correct phrase collocations and four incorrect ones. MAIN OUTCOME MEASURES： Event-related potentials were recorded in the subjects while they read correct or incorrect phases flashed upon a video screen. RESULTS： Both verbs and prepositions elicited negativity at the frontal site in a 230-330 ms window, as well as at the fronto-temporal and central sites in a 350-500 ms window. Neither exhibited significant differences in peak [F（1, 15） = 0.144, P = 0.710] and latency [F（1, 15） = 0.144, P= 0.710]. Both verbs and prepositions elicited negativity at the left and right hemisphere in a 270-400 ms window. CONCLUSION： There was no significant difference between Chinese prepositions and verbs in the neural system process and N280 was not the specific component for closed-class words.

WordNet综述

WordNet是一个在线的词典参照系统 ,它是在当前基于人类词汇记忆的心理语言学理论推动下产生的。这个系统中的名词、动词和形容词都聚类为代表某一基本词汇概念的同义词集合 。

基于WordNet的无导词义消歧方法

有导词义消歧机器学习方法由于需要大量人力进行词义标注,难以适用于大规模词义消歧任务.提出一种避免人工词义标注的无导消歧方法.该方法综合利用WordNet知识库中的多种知识源(包括:词义定义描述、使用实例、结构化语义关系、领域属性等)描述歧义词的词义信息,生成词义的"代表词汇集"和"领域代表词汇集",结合词汇的词频分布信息和所处的上下文环境进行词义判定.利用通用测试集Senseval-3对6个典型的无导词义消歧方法进行开放实验,该方法取得平均正确率为49.93%的消歧结果.

基于LDA和word2vec的英文作文跑题检测

针对目前国内的英语作文辅助批阅系统缺少准确而高效的跑题检测算法的问题,提出了一种结合LDA和word2vec的跑题检测算法。该算法利用LDA模型对文档建模并通过word2vec对文档进行训练,利用得到的文档主题和词语之间的语义关系,对文档中各主题及其特征词计算概率加权和,最终通过设定合理阈值筛选出跑题作文。实验中通过改变文档的主题数而得到不同的F值,确定了最佳主题数。实验结果表明,所提出的方法比基于向量空间模型的方法更具有效性,可以检测到更多的跑题作文,并且准确率较高,F值达到89%以上,实现了作文跑题检测的智能化处理,可以有效地应用在英语作文教学中。

θ-improved limited tolerance relation model of incomplete information system for evaluation of water conservancy project management modernization

The modernization of water conservancy project management is a complicated engineering system involving a management system, a management method, management personnel, the exertion of social, economic, and ecological effects, and so on. However, indices for evaluating the modernization of water conservancy project management are usually unobtainable in practical applications. Conducting appropriate extension of the classical rough set theory and then applying it to an incomplete information system are the key to the application of the rough set theory Based on analysis of some extended rough set models in incomplete information systems, a rough set model based on the θ-improved limited tolerance relation is put forward. At the same time, upper approximation and lower approximation are defined under this improved relation. According to the evaluation index system and management practices, the threshold for θ is defined. An example study indicates the practicability and maneuverability of the model.

基于Word Embedding的软件工程领域语义相关词挖掘方法

软件的开发及维护过程中经常要对代码进行搜索。基于关键字匹配的代码搜索面临与传统信息检索一样的问题,即用户查询关键字与代码文本用词不匹配。为提高代码搜索精度,需要挖掘软件中的语义相关词进行查询扩展。本文针对软件工程领域设计了一种基于Word Embedding的语义相关词挖掘方法,并且采用IT技术问答网站Stack Overflow的文档作为语料库训练得到了共包含19332个单词的语义相关词表。与前人工作的对比实验验证了本文方法挖掘的语义相关词能有效提高代码搜索精度。

Lexical Relations： Measuring the Proficiency of the Saudi EFL Learners and Analysing the Obstacles

As teachers of EFL （English as a Foreign Language） in the Kingdom of Saudi Arabia, we are sometimes flabbergasted by the errors that the/earners make in their English scripts. Apparently, there was no pattern to these errors. However, when the researcher observed the frequency of similar error over a few years of her experience as an EFL faculty for Saudi learners, the theory of Lexical Relations appeared to offer an answer. Therein also lies the genesis of the current study. In a positive development, the study did bring to light certain factors that directly played a role in the Saudi EFL learners＇ English errors. These have been presented in this paper with the hope that with the diagnosis in hand, it will be easier for the EFL teachers to find a solution to the dearth of English proficiency among the Saudi EFL learners.

Application of Word Embedding to Drug Repositioning

As a key technology of rapid and low-cost drug development, drug repositioning is getting popular. In this study, a text mining approach to the discovery of unknown drug-disease relation was tested. Using a word embedding algorithm, senses of over 1.7 million words were well represented in sufficiently short feature vectors. Through various analysis including clustering and classification, feasibility of our approach was tested. Finally, our trained classification model achieved 87.6% accuracy in the prediction of drug-disease relation in cancer treatment and succeeded in discovering novel drug-disease relations that were actually reported in recent studies.

Role of the Dorsal Anterior Cingulate Cortex in Relational Memory Formation: A Deep Brain Activity Index Study

The dorsal area of the anterior cingulate cortex (ACC) constructs the salience network associated with the anterior insular cortex. Conventional brain imaging studies, such as functional magnetic resonance imaging (fMRI), have demonstrated that relational memory formation occurs in the ACC. However, how such memory is encoded and retrieved remains unknown due to limited time resolution of conventional fMRI. This study aimed to investigate temporal dynamics of the dorsal ACC (dACC) during word-pair tasks based on a newly developed event-related deep brain activity (ER-DBA) method using occipital electroencephalogram (EEG) signal powers. The method assesses dACC activity at a temporal resolution of approximately 0.3 s beyond the conventional resolution limit. We found that transient deactivation of dACC during the presentation of the second word of each pair was essential for encoding success regardless of whether the words were related or unrelated. We also found that memory accuracy was not affected by the intervention of inter-trials until the recall trial. Taken together, these findings suggest that dACC deactivation for encoding success is accompanied with short-term potentiation essential for durability of memory. We further found that false memory formation associated with the presentation of word pairs was occasionally committed. In such cases, dACC exhibited a similar transient deactivation although false memory commission was independent of related or unrelated conditions. Our findings suggest that encoding and retrieval of associates are paralleled and that simultaneous production of associates seems to be an essential strategy for successful relational memory formation. The study was limited to the assessment of dACC activity and did not account for other regional brain activities or receptor regulation related to short-term potentiation. We detected fast behavior of dACC during relational memory formation using the novel ER-DBA method. Such temporal dynamics will be important for eliciting underlying mechanisms of memory dysfunctions.

老年性聋患者人工耳蜗植入效果分析

目的 探究老年性聋患者人工耳蜗植入术后听觉言语康复效果及生活质量的变化。方法 对31例行人工耳蜗植入的老年性聋患者进行听力学、言语功能及生活质量评估并比较差异。听力学评估采用助听听阈,言语能力评估采用词表识别率,评估时间为术前、开机后6个月及开机后12个月。生活质量评估采用Nijmegen人工耳蜗植入量表(NCIQ),评估时间为术前及开机后12个月。结果 共纳入31例患者,31例患者术前、开机后6个月及开机后12个月助听听阈分别为(62.55±3.69)、(46.58±5.14)、(38.68±4.26)dBHL,差异具有统计学意义(P<0.05)。术前、开机后6个月及开机后12个月单音节词识别率分别为(9.55±5.81)%、(54.77±8.90)%、(68.52±7.21)%,差异具有统计学意义(P<0.05);术前、开机后6个月及开机后12个月双音节词识别率分别为(19.87±9.72)%、(64.00±6.53)%、(74.26±6.79)%,差异具有统计学意义(P<0.05);术前、开机后6个月及开机后12个月短句识别率分别为(28.00±10.58)%、(68.52±7.78)%、(77.61±8.59)%,差异具有统计学意义(P<0.05)。术前及开机12个月NCIQ总量表得分分别为(35.90±5.80)、(65.16±8.18)分,差异具有统计学意义(P<0.05)。结论 人工耳蜗植入可以改善老年性聋患者的听觉言语能力及生活质量,对于重度以上听力损失且助听器效果不佳的老年性聋患者可以选择人工耳蜗植入。

基于BERT的两次注意力机制远程监督关系抽取

针对词向量语义信息不完整以及文本特征抽取时的一词多义问题,提出基于BERT(Bidirectional Encoder Representation from Transformer)的两次注意力加权算法(TARE)。首先,在词向量编码阶段,通过构建Q、K、V矩阵使用自注意力机制动态编码算法,为当前词的词向量捕获文本前后词语义信息;其次,在模型输出句子级特征向量后,利用定位信息符提取全连接层对应参数,构建关系注意力矩阵;最后,运用句子级注意力机制算法为每个句子级特征向量添加不同的注意力分数,提高句子级特征的抗噪能力。实验结果表明:在NYT-10m数据集上,与基于对比学习框架的CIL(Contrastive Instance Learning)算法相比,TARE的F1值提升了4.0个百分点,按置信度降序排列后前100、200和300条数据精准率Precision@N的平均值(P@M)提升了11.3个百分点;在NYT-10d数据集上,与基于注意力机制的PCNN-ATT(Piecewise Convolutional Neural Network algorithm based on ATTention mechanism)算法相比,精准率与召回率曲线下的面积(AUC)提升了4.8个百分点,P@M值提升了2.1个百分点。在主流的远程监督关系抽取(DSER)任务中,TARE有效地提升了模型对数据特征的学习能力。

融合词语语义与标签依赖的隐式篇章关系识别

中文隐式篇章关系识别旨在推断出两个论元间的篇章关系类型。然而,现有的方法往往忽略了论元中词语所蕴含的关键信息,并且仅考虑单个层级内的篇章关系类型,忽略了各层级间篇章关系的依赖关联。鉴于此,提出融合词语语义和标签依赖的方法,以序列生成的方式实现篇章关系识别,先根据相似度权重将词向量嵌入到字编码表示中,应用字词对齐注意力机制强调关键字、词信息,再采用标签注意力编码从蕴含词语语义的论元表示和篇章关系表示中获取篇章关系依赖性的上下文表示,以自下而上的方式预测顶层的篇章关系类型。此外,构建面向阅读理解篇章的篇章关系数据集,并在该数据集上展开实验,结果显示隐式篇章关系识别准确率和F1值分别达到74.19%和73.81%,最终验证了该方法的有效性。

基于深度字词融合的小麦种质信息实体关系联合抽取

为获得结构化的小麦品种表型和遗传描述,针对非结构化小麦种质数据中存在的实体边界模糊以及关系重叠问题,提出一种基于深度字词融合的小麦种质信息实体关系联合抽取模型WGIE-DCWF(wheat germplasm information extraction model based on deep character and word fusion)。模型编码层通过深度字词融合和上下文语义特征融合,提高密集实体特征识别能力;模型三元组抽取层建立层叠指针网络,提高重叠关系的提取能力。在小麦种质数据集和公开数据集上的一系列对比实验结果表明,WGIE-DCWF模型能够有效提高小麦种质数据实体关系联合抽取效果,同时拥有较好的泛化性,可以为小麦种质信息知识库构建提供技术支撑。