检索结果-南通市图书馆

Battle Royale Optimization with Fuzzy Deep Learning for Arabic Sentiment Classification

Computer Systems Science & Engineering 2023年第8期46卷 2619-2635页

作者： Manar Ahmed Hamza Hala J.Alshahrani Jaber S.alzahrani Heba Mohsen Mohamed I.Eldesouki Mohammed Rizwanullah Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Applied Linguistics College of LanguagesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMakkah 24211Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Aspect-Based Sentiment Analysis(ABsa)on Arabic corpus has become an active research topic in recent *** refers to a fine-grained Sentiment Analysis(sa)task that focuses on the extraction of the conferred aspects and the identification of respective sentiment polarity from the provided *** of the prevailing Arabic ABsa techniques heavily depend upon dreary feature-engineering and pre-processing tasks and utilize external sources such as *** literature,concerning the Arabic language text analysis,the authors made use of regular Machine Learning(ML)techniques that rely on a group of rare sources and *** sources were used for processing and analyzing the Arabic language content like ***,an important challenge in this domain is the unavailability of sufficient and reliable *** this background,the current study introduces a new Battle Royale Optimization with Fuzzy Deep Learning for Arabic Aspect Based Sentiment Classification(BROFDL-AASC)*** aim of the presented BROFDL-AASC model is to detect and classify the sentiments in the Arabic *** the presented BROFDL-AASC model,data pre-processing is performed at first to convert the input data into a useful ***,the BROFDL-AASC model includes Discriminative Fuzzy-based Restricted Boltzmann Machine(DFRBM)model for the identification and categorization of ***,the BRO algorithm is exploited for optimal fine-tuning of the hyperparameters related to the FBRBM *** scenario establishes the novelty of current *** performance of the proposed BROFDL-AASC model was validated and the outcomes demonstrate the supremacy of BROFDL-AASC model over other existing models.

关键词： Arabic corpus aspect based sentiment analysis arabic language deep learning battle royale optimization natural language processing

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Parameter Tuned Machine Learning Based Emotion Recognition on Arabic Twitter Data

引用

Computer Systems Science & Engineering 2023年第9期46卷 3423-3438页

作者： Ibrahim M.Alwayle Badriyya B.Al-onazi Jaber S.alzahrani Khaled M.Alalayah Khadija M.Alaidarous Ibrahim Abdulrab Ahmed Mahmoud Othman Abdelwahed Motwakel Department of Computer Science College of Science and ArtsSharurahNajran UniversityNajran55461Saudi Arabia Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityNajran24211Saudi Arabia Computer Department Applied CollegeNajran UniversityNajran66462Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Arabic is one of the most spoken languages across the ***,there are fewer studies concerning Sentiment Analysis(sa)in *** recent years,the detected sentiments and emotions expressed in tweets have received significant *** substantial role played by the Arab region in international politics and the global economy has urged the need to examine the sentiments and emotions in the Arabic *** common models are available:Machine Learning and lexicon-based approaches to address emotion classification *** this motivation,the current research article develops a Teaching and Learning Optimization with Machine Learning Based Emotion Recognition and Classification(TLBOML-ERC)model for Sentiment Analysis on tweets made in the Arabic *** presented TLBOML-ERC model focuses on recognising emotions and sentiments expressed in Arabic *** attain this,the proposed TLBOMLERC model initially carries out data pre-processing and a Continuous Bag Of Words(CBOW)-based word embedding *** addition,Denoising Autoencoder(DAE)model is also exploited to categorise different emotions expressed in Arabic *** improve the efficacy of the DAE model,the Teaching and Learning-based Optimization(TLBO)algorithm is utilized to optimize the *** proposed TLBOML-ERC method was experimentally validated with the help of an Arabic tweets *** obtained results show the promising performance of the proposed TLBOML-ERC model on Arabic emotion classification.

关键词： Arabic language Twitter data machine learning teaching and learning-based optimization sentiment analysis emotion classification

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Multi-Versus Optimization with Deep Reinforcement Learning Enabled Affect Analysis on Arabic Corpus

引用

Computer Systems Science & Engineering 2023年第12期47卷 3049-3065页

作者： Mesfer Al Duhayyim Badriyya B.Al-onazi Jaber S.alzahrani Hussain Alshahrani Mohamed Ahmed Elfaki Abdullah Mohamed Ishfaq Yaseen Gouse Pasha Mohammed Mohammed Rizwanullah Abu sarwar Zamani Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAflaj16273Saudi Arabia Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMakkah24211Saudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Sentiment analysis(sa)of the Arabic language becomes important despite scarce annotated corpora and confined *** affect Analysis has become an active research zone *** still,the Arabic language lags behind adequate language sources for enabling the sa ***,Arabic still faces challenges in natural language processing(NLP)tasks because of its structure complexities,history,and distinct *** has gained lesser effort than the other *** paper developed a Multi-versus Optimization with Deep Reinforcement Learning Enabled Affect Analysis(MVODRL-AA)on Arabic *** presented MVODRL-AAmodelmajorly concentrates on identifying and classifying effects or emotions that occurred in the Arabic ***,the MVODRL-AA model follows data pre-processing and word ***,an n-gram model is utilized to generate word embeddings.A deep Q-learning network(DQLN)model is then exploited to identify and classify the effect on the Arabic *** last,the MVO algorithm is used as a hyperparameter tuning approach to adjust the hyperparameters related to the DQLN model,showing the novelty of the work.A series of simulations were carried out to exhibit the promising performance of the MVODRL-AA *** simulation outcomes illustrate the betterment of the MVODRL-AA method over the other approaches with an accuracy of 99.27%.

关键词： Arabic language Arabic corpus natural language processing affect analysis deep learning

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

A Reliable NLP Scheme for English Text Watermarking Based on Contents Interrelationship

引用

Computer Systems Science & Engineering 2021年第6期37卷 297-311页

作者： Fahd N.Al-Wesabi sa.eh alzahrani Fuad Alyarimi Mohammed Abdul Nadhem Nemri Mohammed M.Almazah Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Information Systems King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Department of Mathematics and computer in Ibb University Yemen and Department of MathematicsKing Khalid UniversityMuhayel AseerKingdom of Saudi Arabia

In this paper,a combined approach CAZWNLP(a combined approach of zero-watermarking and natural language processing)has been developed for the tampering detection of English text exchanged through the *** third gram of alphanumeric of the Markov model has been used with text-watermarking technologies to improve the performance and accuracy of tampering detection issues which are limited by the existing works reviewed in the literature of this *** third-grade level of the Markov model has been used in this method as natural language processing technology to analyze an English text and extract the textual characteristics of the given ***,the extracted features have been utilized as watermark information and then validated with the attacked English text to detect any suspected tampering occurred on *** embedding mechanism of CAZWNLP method will be achieved logically without effects or modifying the original text document to embed a watermark *** has been implemented using VS code IDE with *** experimental and simulation results using standard datasets of varying lengths show that the proposed approach can obtain high robustness and better detection accuracy of tampering common random insertion,reorder,and deletion attacks,e.g.,Comparison results with baseline approaches also show the advantages of the proposed approach.

关键词： NLP text analysis English text watermarking robustness tampering detection

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Arabic Feature-Based Text Watermarking Technique for Sensitive Detecting Tampering Attack

引用

Computers, Materials & Continua 2021年第9期68卷 3789-3806页

作者： Fahd N.Al-Wesabi Huda G.Iskandar sa.eh alzahrani Abdelzahir Abdelmaboud Mohammed Abdul Nadhem Nemri Mohammad Medani Mohammed Y.Alghamdi Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen School of Computing Faculty of EngineeringUniversiti Teknologi MalaysiaMalaysia Department of Information Systems King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Department of Computer Science Faculty of Science&Arts of BaljurshiAl-Baha UniversityKSA

In this article,a high-sensitive approach for detecting tampering attacks on transmitted Arabic-text over the Internet(HFDATAI)is proposed by integrating digital watermarking and hidden Markov model as a strategy for soft *** HFDATAI solution technically integrates and senses the watermark without modifying the original *** alphanumeric mechanism order in the first stage focused on the Markov model key secret is incorporated into an automated,null-watermarking approach to enhance the proposed approach’s efficiency,accuracy,and *** first-level order and alphanumeric Markov model technique have been used as a strategy for soft computing to analyze the text of the Arabic *** addition,the features of the interrelationship among text contexts and characteristics of watermark information extraction that is used later validated for detecting any tampering of the Arabic-text *** HFDATAI strategy was introduced based on PHP with included IDE of VS *** of four separate duration datasets in random sites illustrate the fragility,efficacy,and applicability of HFDATAI by using the three common tampering attacks i.e.,insertion,reorder,and *** HFDATAI was found to be effective,applicable,and very sensitive for detecting any possible tampering on Arabic text.

关键词： Watermarking soft computing text analysis hidden Markov model content authentication

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

An Optimized Design of Antenna Arrays for the Smart Antenna Systems

引用

Computers, Materials & Continua 2021年第11期69卷 1979-1994页

作者： Fahd N.Al-Wesabi Murad A.A.Almekhlafi Huda G.Iskandar Adnan Zain sa.eh alzahrani Mohammed Alamgeer Nadhem Nemri sami Dhabi Mohammad Medani Ali.M.Al-Sharafi Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Electrical Engineering–Communication Engineering Sana’a UniversityYemen School of Computing Faculty of EngineeringUniversiti Teknologi MalaysiaMalaysia Department of Electronics and Communication Engineering Faculty of EngineeringUniversity of AdenYemen Department of Information Systems King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Department of Computer Science College of Computers and Information TechnologyUniversity of BishaKSA

In recent years,there has been an increasing demand to improve cellular communication services in several *** aspect that received the most attention is improving the quality of coverage through using smart antennas which consist of array *** paper investigates the main characteristics and design of the three types of array antennas of the base station for better coverage through simulation(MATLAB)which provides field and strength patterns measured in polar and rectangular coordinates for a variety of conditions including broadsides,ordinary End-fire,and increasing directivity End-fire which is typically used in smart *** method of analysis was applied to twenty experiments of process design to each antenna type separately,so sixty results were obtained from the radiation pattern indicating the parameters for each radiation ***,nineteen design experiments were described in this *** is hoped that the results obtained from this study will help engineers solve coverage problems as well as improve the quality of cellular communication networks.

关键词： Smart antenna antenna arrays patterns construction coverage

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：