Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (106)
  • Open Access

    ARTICLE

    Automated Spam Review Detection Using Hybrid Deep Learning on Arabic Opinions

    Ibrahim M. Alwayle1, Badriyya B. Al-onazi2, Mohamed K. Nour3, Khaled M. Alalayah1, Khadija M. Alaidarous1, Ibrahim Abdulrab Ahmed4, Amal S. Mehanna5, Abdelwahed Motwakel6,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2947-2961, 2023, DOI:10.32604/csse.2023.034456

    Abstract Online reviews regarding purchasing services or products offered are the main source of users’ opinions. To gain fame or profit, generally, spam reviews are written to demote or promote certain targeted products or services. This practice is called review spamming. During the last few years, various techniques have been recommended to solve the problem of spam reviews. Previous spam detection study focuses on English reviews, with a lesser interest in other languages. Spam review detection in Arabic online sources is an innovative topic despite the vast amount of data produced. Thus, this study develops an Automated Spam Review Detection using… More >

  • Open Access

    ARTICLE

    Covid-19 Detection Using Deep Correlation-Grey Wolf Optimizer

    K. S. Bhuvaneshwari1, Ahmed Najat Ahmed2, Mehedi Masud3, Samah H. Alajmani4, Mohamed Abouhawwash5,6,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2933-2945, 2023, DOI:10.32604/csse.2023.034288

    Abstract The immediate and quick spread of the coronavirus has become a life-threatening disease around the globe. The widespread illness has dramatically changed almost all sectors, moving from offline to online, resulting in a new normal lifestyle for people. The impact of coronavirus is tremendous in the healthcare sector, which has experienced a decline in the first quarter of 2020. This pandemic has created an urge to use computer-aided diagnosis techniques for classifying the Covid-19 dataset to reduce the burden of clinical results. The current situation motivated me to choose correlation-based development called correlation-based grey wolf optimizer to perform accurate classification.… More >

  • Open Access

    ARTICLE

    Improved Ant Lion Optimizer with Deep Learning Driven Arabic Hate Speech Detection

    Abdelwahed Motwakel1,*, Badriyya B. Al-onazi2, Jaber S. Alzahrani3, Sana Alazwari4, Mahmoud Othman5, Abu Sarwar Zamani1, Ishfaq Yaseen1, Amgad Atta Abdelmageed1

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3321-3338, 2023, DOI:10.32604/csse.2023.033901

    Abstract Arabic is the world’s first language, categorized by its rich and complicated grammatical formats. Furthermore, the Arabic morphology can be perplexing because nearly 10,000 roots and 900 patterns were the basis for verbs and nouns. The Arabic language consists of distinct variations utilized in a community and particular situations. Social media sites are a medium for expressing opinions and social phenomena like racism, hatred, offensive language, and all kinds of verbal violence. Such conduct does not impact particular nations, communities, or groups only, extending beyond such areas into people’s everyday lives. This study introduces an Improved Ant Lion Optimizer with… More >

  • Open Access

    ARTICLE

    Hunter Prey Optimization with Hybrid Deep Learning for Fake News Detection on Arabic Corpus

    Hala J. Alshahrani1, Abdulkhaleq Q. A. Hassan2, Khaled Tarmissi3, Amal S. Mehanna4, Abdelwahed Motwakel5,*, Ishfaq Yaseen5, Amgad Atta Abdelmageed5, Mohamed I. Eldesouki6

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4255-4272, 2023, DOI:10.32604/cmc.2023.034821

    Abstract Nowadays, the usage of social media platforms is rapidly increasing, and rumours or false information are also rising, especially among Arab nations. This false information is harmful to society and individuals. Blocking and detecting the spread of fake news in Arabic becomes critical. Several artificial intelligence (AI) methods, including contemporary transformer techniques, BERT, were used to detect fake news. Thus, fake news in Arabic is identified by utilizing AI approaches. This article develops a new hunter-prey optimization with hybrid deep learning-based fake news detection (HPOHDL-FND) model on the Arabic corpus. The HPOHDL-FND technique undergoes extensive data pre-processing steps to transform… More >

  • Open Access

    ARTICLE

    Applied Linguistics with Mixed Leader Optimizer Based English Text Summarization Model

    Hala J. Alshahrani1, Khaled Tarmissi2, Ayman Yafoz3, Abdullah Mohamed4, Manar Ahmed Hamza5,*, Ishfaq Yaseen5, Abu Sarwar Zamani5, Mohammad Mahzari6

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3203-3219, 2023, DOI:10.32604/iasc.2023.034848

    Abstract The term ‘executed linguistics’ corresponds to an interdisciplinary domain in which the solutions are identified and provided for real-time language-related problems. The exponential generation of text data on the Internet must be leveraged to gain knowledgeable insights. The extraction of meaningful insights from text data is crucial since it can provide value-added solutions for business organizations and end-users. The Automatic Text Summarization (ATS) process reduces the primary size of the text without losing any basic components of the data. The current study introduces an Applied Linguistics-based English Text Summarization using a Mixed Leader-Based Optimizer with Deep Learning (ALTS-MLODL) model. The… More >

  • Open Access

    ARTICLE

    Deep Learning Driven Arabic Text to Speech Synthesizer for Visually Challenged People

    Mrim M. Alnfiai1,2, Nabil Almalki1,3, Fahd N. Al-Wesabi4,*, Mesfer Alduhayyem5, Anwer Mustafa Hilal6, Manar Ahmed Hamza6

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2639-2652, 2023, DOI:10.32604/iasc.2023.034069

    Abstract Text-To-Speech (TTS) is a speech processing tool that is highly helpful for visually-challenged people. The TTS tool is applied to transform the texts into human-like sounds. However, it is highly challenging to accomplish the TTS outcomes for the non-diacritized text of the Arabic language since it has multiple unique features and rules. Some special characters like gemination and diacritic signs that correspondingly indicate consonant doubling and short vowels greatly impact the precise pronunciation of the Arabic language. But, such signs are not frequently used in the texts written in the Arabic language since its speakers and readers can guess them… More >

  • Open Access

    ARTICLE

    Political Optimizer with Probabilistic Neural Network-Based Arabic Comparative Opinion Mining

    Najm Alotaibi1, Badriyya B. Al-onazi2, Mohamed K. Nour3, Abdullah Mohamed4, Abdelwahed Motwakel5,*, Gouse Pasha Mohammed5, Ishfaq Yaseen5, Mohammed Rizwanullah5

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3121-3137, 2023, DOI:10.32604/iasc.2023.033915

    Abstract Opinion Mining (OM) studies in Arabic are limited though it is one of the most extensively-spoken languages worldwide. Though the interest in OM studies in the Arabic language is growing among researchers, it needs a vast number of investigations due to the unique morphological principles of the language. Arabic OM studies experience multiple challenges owing to the poor existence of language sources and Arabic-specific linguistic features. The comparative OM studies in the English language are wide and novel. But, comparative OM studies in the Arabic language are yet to be established and are still in a nascent stage. The unique… More >

  • Open Access

    ARTICLE

    Leveraging Retinal Fundus Images with Deep Learning for Diabetic Retinopathy Grading and Classification

    Mohammad Yamin1,*, Sarah Basahel1, Saleh Bajaba2, Mona Abusurrah3, E. Laxmi Lydia4

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1901-1916, 2023, DOI:10.32604/csse.2023.036455

    Abstract Recently, there has been a considerable rise in the number of diabetic patients suffering from diabetic retinopathy (DR). DR is one of the most chronic diseases and makes the key cause of vision loss in middle-aged people in the developed world. Initial detection of DR becomes necessary for decreasing the disease severity by making use of retinal fundus images. This article introduces a Deep Learning Enabled Large Scale Healthcare Decision Making for Diabetic Retinopathy (DLLSHDM-DR) on Retinal Fundus Images. The proposed DLLSHDM-DR technique intends to assist physicians with the DR decision-making method. In the DLLSHDM-DR technique, image preprocessing is initially… More >

  • Open Access

    ARTICLE

    Harris Hawks Optimizer with Graph Convolutional Network Based Weed Detection in Precision Agriculture

    Saud Yonbawi1, Sultan Alahmari2, T. Satyanarayana Murthy3, Padmakar Maddala4, E. Laxmi Lydia5, Seifedine Kadry6,7,8,*, Jungeun Kim9

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1533-1547, 2023, DOI:10.32604/csse.2023.036296

    Abstract Precision agriculture includes the optimum and adequate use of resources depending on several variables that govern crop yield. Precision agriculture offers a novel solution utilizing a systematic technique for current agricultural problems like balancing production and environmental concerns. Weed control has become one of the significant problems in the agricultural sector. In traditional weed control, the entire field is treated uniformly by spraying the soil, a single herbicide dose, weed, and crops in the same way. For more precise farming, robots could accomplish targeted weed treatment if they could specifically find the location of the dispensable plant and identify the… More >

  • Open Access

    ARTICLE

    A Multimodel Transfer-Learning-Based Car Price Prediction Model with an Automatic Fuzzy Logic Parameter Optimizer

    Ping-Huan Kuo1,2, Sing-Yan Chen1, Her-Terng Yau1,2,*

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1577-1596, 2023, DOI:10.32604/csse.2023.036292

    Abstract Cars are regarded as an indispensable means of transportation in Taiwan. Several studies have indicated that the automotive industry has witnessed remarkable advances and that the market of used cars has rapidly expanded. In this study, a price prediction system for used BMW cars was developed. Nine parameters of used cars, including their model, registration year, and transmission style, were analyzed. The data obtained were then divided into three subsets. The first subset was used to compare the results of each algorithm. The predicted values produced by the two algorithms with the most satisfactory results were used as the input… More >

Displaying 21-30 on page 3 of 106. Per Page