Next Words Prediction and Sentence Completion in Bangla Language Using GRU-Based RNN on N-Gram Language Model

We use a lot of devices in our daily life to communicate with others. In this modern world, people use email, Facebook, Twitter, and many other social network sites for exchanging information. People lose their valuable time misspelling and retyping, and some people are not happy to type large sentences because they face unnecessary words or grammatical issues. So, for this reason, word predictive systems help to exchange textual information more quickly, easier, and comfortably for all people. These systems predict the next most probable words and give users to choose of the needed word from these suggested words. Word prediction can help the writer by predicting the next word and helping complete the sentence correctly. This research aims to forecast the most suitable next word to complete a sentence for any given context. In this research, we have worked on the Bangla language. We have presented a process that can expect the next maximum probable and proper words and suggest a complete sentence using predicted words. In this research, GRU-based RNN has been used on the N-gram dataset to develop the proposed model. We collected a large dataset using multiple sources in the Bangla language and also compared it to the other approaches that have been used such as LSTM, and Naive Bayes. But this suggested approach provides excellent exactness than others. Here, the Unigram model provides 88.22%, Bi-gram model is 99.24%, Tri-gram model is 97.69%, and 4-gram and 5-gram models provide 99.43% and 99.78% on average accurateness. We think that our proposed method profound impression on Bangla search engines.

A Study on the English Translation of Culture-Loaded Words From the Perspective of Relevance-Theoretic Translation Theory-A Case Study of Yang Xianyi’s The True Story of Ah Q

Culture-loaded words reveal the basic features of a country’s social life,customs and habits,religious beliefs,and so on.The meanings of culture-loaded words contain the profound cultural connotation of a country or a nation.However,due to the influence of different cultures,the original author and the target readers lack a common cognitive context,which means they cannot successfully conduct a cultural communication.Therefore,correctly understanding and translating these culture-loaded words have become a major problem for translators in the translation process of literary works.Under the guidance of the dual ostensive-inferential model in relevance-theoretical translation theory,this paper,by emphasizing the importance of common cognitive context to a successful translation,analyzes the translation process of five categories of culture-loaded words and summarizes the translation strategies that can accurately convey the writing intention of the original author,which provides a new perspective for the translation of culture-loaded words.

The Translation Strategies of Chinese Reduplicated Words From a Skopos Theory Perspective

This paper explores the translation strategies for Chinese reduplication to English from the perspective of Skopos theory. Drawing on previous research on the semantic functions of reduplication, the paper analyzes the three main types of semantic changes in Chinese reduplicated words: intensification of meaning, moderation of meaning, and addition of meaning. The paper then proposes different translation strategies for Chinese reduplication, including same-word repetition, near-synonym repetition, “have a try” form, “noun(pl.) + of” form, and “all”, “each”, and “every” pattern. Finally, the paper emphasizes the importance of understanding the intended communicative function of the reduplicated words and the need for flexible handling in order to achieve a natural translation with better readability.

A Study on German Translation Strategies of Culture-Loaded Words in Documentary Hexi Corridor(Expert)by Adaptation Theory

This paper deals with the translation strategies of Chinese Culture-Loaded Words from the perspective of adaptation theory.It is based on the translation text of the sixth episode“Silk Road”and the seventh episode“Dunhuang”of the documentary Hexi Corridor.Many words with Chinese cultural connotations appear in the subtitles of this documentary.This paper will be divided into four parts.The first part and the second part deal with the basic theories,i.e.,definition of Chinese Culture-Loaded Words and of adaptation theory.The original text is analysed in the third part.This part deals with the background and specifics of the language of the documentary film Hexi Corridor.The fourth part deals with the difficulties encountered by the author in translation practice and the corresponding solutions adopted by the author.The translation difficulties are solved by five translation methods,namely transliteration,loan translation,substitution,interpretation,and adaptation.

Python实现Excel文档转换到Word文档的自动化方法

通过研究开发了一种基于Python语言,实现Excel数据自动转换成Word文档并实现排版功能的方法,为科研工作者、数据分析师或报告撰写人员提供一个方便快捷的工具,帮助他们更高效地完成Excel数据转换成Word并实现排版的任务。

基于图像Bag-of-Words模型的无载体信息隐藏

介绍一种基于bag-of-words(BOW)模型的无载体信息隐藏方法.该方法使用BOW模型提取图像的视觉关键词(visual words,VW)以表达待隐藏的文本信息,从而实现文本信息在图像中的隐藏.首先使用BOW模型提取图像集中每幅图像的VW,构建文本信息的关键词和VW的映射关系库;然后把每幅图像分为若干子图像,统计每一幅子图像的VW频数直方图,选择频数最高的VW表示该子图像;最后根据构建的文本关键词和子图像VW的映射关系库,搜索出与待隐藏文本信息存在映射关系的子图像序列,将含有这些子图像的图像作为含密图像进行传递.实验结果和分析表明,该隐藏算法在抗隐写分析、鲁棒性和安全性方面均有良好的表现.

基于“bag of words”的视频匹配方法

提出了一种利用"bag of words"模型对视频内容进行建模和匹配的方法。通过量化视频帧的局部特征构建视觉关键词(visual words)辞典,将视频的子镜头表示成若干视觉关键词的集合。在此基础上构建基于子镜头的视觉关键词词组的倒排索引,用于视频片段的匹配和检索。这种方法保留了局部特征的显著性及其相对位置关系,而且有效地压缩了视频的表达,加速的视频的匹配和检索过程。实验结果表明,和已有方法相比,基于"bag of words"的视频匹配方法在大视频样本库上获得了更高的检索精度和检索速度。

基于神经网络词嵌入的大数据关注热点和词嵌入概貌比较研究

[目的/意义]大数据对社会和经济发展产生了重大影响,本研究结合我国学术平台和社会化问答平台对大数据关注热点和词嵌入概貌进行比较,旨在推动我国大数据研究和实践。[方法/过程]Word2vec是新兴的神经网络词嵌入算法,具有计算成本低、准确度高等特点,能够同时在语义层面和语法层面有效测度词语的相似度。首先,结合中国知网和知乎平台分别搜集了数据,构建出学术平台和社会化问答平台的语料库,再基于这两个语料库分别训练了Word2vec模型;其次,结合最相似词语分析对学术平台和社会化问答平台的大数据关注热点进行了比较;最后,利用降维技术和数据可视化方法对两个平台词语的词嵌入概貌进行了比较。[结果/结论]研究结果显示了我国学术平台和社会化问答平台在大数据方面的差异。本研究创新地利用Word2vec神经网络词嵌入算法,结合我国学术平台和社会化问答平台对大数据进行了比较分析,为大数据研究提供了新的视角。

编委对期刊研究主题的影响研究——以信息科学领域为例

[目的/意义]学术期刊是学术交流的重要载体之一,期刊编委团队承担着把握期刊方向的重要职责,并对期刊发文内容和发文质量进行把关。期刊编委的研究主题能够体现编委对本领域学术动态的觉察和感知,本文旨在探究编委的研究主题对期刊收录文章主题的影响情况。[方法/过程]以信息科学领域一流期刊为研究对象,构建编委数据集和非编委数据集,通过数据集信息挖掘期刊收录文章主题,利用Word2Vec模型和Kmeans聚类方法探究期刊内的主题分布特征,探究编委的主题影响情况。[结果/结论]研究发现编委对冷门主题的影响高于热门主题,编委能够通过在新兴主题集中性发文引导期刊的研究主题发生变化,引导学者对有价值的主题进行研究。

基于LDA-Word2vec的图书情报领域机器学习研究主题演化与热点主题识别

[目的/意义]在人工智能技术及应用快速发展与深刻变革背景下,机器学习领域不断出现新的研究主题和方法,深度学习和强化学习技术持续发展。因此,有必要探索不同领域机器学习研究主题演化过程,并识别出热点与新兴主题。[方法/过程]本文以图书情报领域中2011—2022年Web of Science数据库中的机器学习研究论文为例,融合LDA和Word2vec方法进行主题建模和主题演化分析,引入主题强度、主题影响力、主题关注度与主题新颖性指标识别热点主题与新兴热点主题。[结果/结论]研究结果表明,(1)Word2vec语义处理能力与LDA主题演化能力的结合能够更加准确地识别研究主题,直观展示研究主题的分阶段演化规律;(2)图书情报领域的机器学习研究主题主要分为自然语言处理与文本分析、数据挖掘与分析、信息与知识服务三大类范畴。各类主题之间的关联性较强,且具有主题关联演化特征;(3)设计的主题强度、主题影响力和主题关注度指标及综合指标能够较好地识别出2011—2014年、2015—2018年和2019—2022年3个不同周期阶段的热点主题。

基于谱聚类的轨道电路故障文本主题聚类研究

轨道电路故障日志是现场日常运维工作中的重要数据记录。针对轨道电路故障日志在现场工作中未能充分挖掘利用且人工分析效率较低的问题,提出基于谱聚类算法的轨道电路故障文本主题聚类挖掘分析方法。首先,分析轨道电路故障文本数据特征并进行文本预处理,采用Word2vec模型训练获取字符级特征向量,实现在语义空间上的轨道电路故障文本数据特征表示;然后,依据Laplacian矩阵的图谱聚类特性,将高维故障文本特征数据聚类转换为谱图切分问题,分别对电务、工务及供电故障因素文本数据求解规范化后Laplacian矩阵的特征向量,并构建低维故障文本特征矩阵,再通过K-Means聚类算法实现3种故障因素文本数据集下故障文本主题聚类分析,获取电务、工务及供电故障因素文本数据中蕴含的轨道电路故障主题类型及频率信息,并基于t分布随机邻域嵌入算法实现聚类结果的可视化分析;最后,采用不同聚类模型在3种故障因素文本数据集上进行对比实验。实验结果表明:基于谱聚类算法的聚类模型在保证故障文本聚类准确率的情况下,其收敛性能更优;聚类可视化分析结果验证了获取的不同故障主题类别具有较高的语义区分度。通过该方法对轨道电路故障文本数据进行自动化聚类挖掘及统计分析,可为现场轨道电路综合维修及故障预防提供辅助支持。

题名相似度模型在文献数据质量控制中的应用

针对特色文献资源建设面临采访预订单中元数据描述不标准、字段不齐全、输入不规范,采访渠道广泛等问题给查重工作带来的难度,本文提出了基于题名相似度的查重模型,将题名经过数据预处理后利用word2vec提取题名的特征向量,计算题名之间的余弦相似度解决文献的查重问题。实验结果表明该查重模型具有较好的效果,为图书馆馆藏特色文献资源建设提供了可行的借鉴。

基于K-means与Word2vec的哺乳文胸评论主题挖掘研究

目的为了了解消费者在网络平台购买哺乳文胸时的关注侧重点,文章从在线评论中抽取有效关键词构建哺乳文胸主题,并通过计算主题的重要程度协助商家了解消费者关注重点方向。方法选用TF-IDF关键词抽取算法,结合K-means和Word2vec进行语义聚类、主题识别、主题词挖掘及主题重要度计算。结果哺乳文胸评论文本聚类后的主题重要程度排名是:产品品质(45.47%)、产品外观(35.83%)、产品服务(18.79%)。结论通过该方法能够有效的识别和构建哺乳文胸主题及主题词,同时,通过主题的重要程度,能够了解消费者对于网络平台购买哺乳文胸时关注的重点方向,为哺乳内衣企业进行产品改善及生产等提供理论参考。

基于Word2Vec和决策树的故障定位技术

利用Word2Vec方法对Java源代码进行深层语义编码,生成文件级和行级的语义向量,并将其用作输入数据来训练决策树模型,以实现精确的文件级别和行级别故障定位,优化故障检测过程,构建一个综合文件级别与行级别分析的高效故障定位框架.实验结果表明:该模型在各项目中的故障定位准确率均高于83%.

基于Word VBA辅助技术文件编制的数字化协同建设的探索

文件编制是设计研发人员日常工作的重要组成部分,其中技术文件的编制涉及大量文件结构和起草规则的应用,基于相关标准中关于文件的编写要求,文章利用WordVBA编程技术辅助技术文件编写工作中的格式编排,实现了Word文档标准格式技术文件的自动化编制,从而保障文件编制符合标准格式要求,有效提高了工作效率。

GUIDE FOR AUTHORS

Introduction Types of paper Contributions falling into the following categories will be considered for publication:Reviews article(>10000 words),Short review(~5000 words),Feature article(>8000 words),Research paper,Short communication(~3000 words),Commentary(~1000 words),and Viewpiont(~3000 words).Please ensure that you select the appropriate article type from the list of options when making your submission.Authors contributing to special issues should ensure that they select the special issue article type from this list.

GUIDE FOR AUTHORS

IntroductionTypes of paper Contributions falling into the following categories will be considered for publication:Reviews article(>10000 words),Short review(~5000 words),Feature article(>8000 words),Research paper,Short communication(~3000 words),Commentary(~1000 words),and Viewpiont(~3000 words).Please ensure that you select the appropriate article type from the list of options when making your submission.Authors contributing to special issues should ensure that they select the special issue article type from this list.

GUIDE FOR AUTHORS

IntroductionTypes of paper Contributions falling into the following categories will be considered for publication:Reviews article(>10000 words),Short review(~5000 words),Feature article(>8000 words),Research paper,Short communication(~3000 words),Commentary(~1000 words),and Viewpiont(~3000 words).Please ensure that you select the appropriate article type from the list of options when making your submission.Authors contributing to special issues should ensure that they select the special issue article type from this list.

GUIDE FOR AUTHORS

Introduction.Types of paper.Contributions falling into the following categories will be considered for publication:Reviews article(>10000 words),Short review(~5000 words),Feature article(>8000 words),Research paper,Short communication(~3000 words),Commentary(~1000 words),and Viewpiont(~3000 words).Please ensure that you select the appropriate article type from the list of options when making your submission.Authors contributing to special issues should ensure that they select the special issue article type from this list.

GUIDE FOR AUTHORS

Contributions falling into the following categories will be considered for publication:Reviews article(>10000 words),Short review(-5000 words),Feature article(>8000 words),Research paper,Short communication(-3000 words),Commentary(-1000 words),and Viewpiont(-3000 words).Please ensure that you select the appropriate article type from the list of options when making your submission.Authors contributing to special issues should ensure that they select the special issue article type from this list.