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  • Open Access

    ARTICLE

    Aspect-Based Sentiment Classification Using Deep Learning and Hybrid of Word Embedding and Contextual Position

    Waqas Ahmad1, Hikmat Ullah Khan1,2,*, Fawaz Khaled Alarfaj3,*, Saqib Iqbal4, Abdullah Mohammad Alomair3, Naif Almusallam3

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3101-3124, 2023, DOI:10.32604/iasc.2023.040614 - 11 September 2023

    Abstract Aspect-based sentiment analysis aims to detect and classify the sentiment polarities as negative, positive, or neutral while associating them with their identified aspects from the corresponding context. In this regard, prior methodologies widely utilize either word embedding or tree-based representations. Meanwhile, the separate use of those deep features such as word embedding and tree-based dependencies has become a significant cause of information loss. Generally, word embedding preserves the syntactic and semantic relations between a couple of terms lying in a sentence. Besides, the tree-based structure conserves the grammatical and logical dependencies of context. In addition,… More >

  • Open Access

    ARTICLE

    Ensemble Deep Learning Framework for Situational Aspects-Based Annotation and Classification of International Student’s Tweets during COVID-19

    Shabir Hussain1, Muhammad Ayoub2, Yang Yu1, Junaid Abdul Wahid1, Akmal Khan3, Dietmar P. F. Moller4, Hou Weiyan1,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5355-5377, 2023, DOI:10.32604/cmc.2023.036779 - 29 April 2023

    Abstract As the COVID-19 pandemic swept the globe, social media platforms became an essential source of information and communication for many. International students, particularly, turned to Twitter to express their struggles and hardships during this difficult time. To better understand the sentiments and experiences of these international students, we developed the Situational Aspect-Based Annotation and Classification (SABAC) text mining framework. This framework uses a three-layer approach, combining baseline Deep Learning (DL) models with Machine Learning (ML) models as meta-classifiers to accurately predict the sentiments and aspects expressed in tweets from our collected Student-COVID-19 dataset. Using the… More >

  • Open Access

    ARTICLE

    Multi-Task Learning Model with Data Augmentation for Arabic Aspect-Based Sentiment Analysis

    Arwa Saif Fadel1,2,*, Osama Ahmed Abulnaja1, Mostafa Elsayed Saleh1

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4419-4444, 2023, DOI:10.32604/cmc.2023.037112 - 31 March 2023

    Abstract Aspect-based sentiment analysis (ABSA) is a fine-grained process. Its fundamental subtasks are aspect term extraction (ATE) and aspect polarity classification (APC), and these subtasks are dependent and closely related. However, most existing works on Arabic ABSA content separately address them, assume that aspect terms are preidentified, or use a pipeline model. Pipeline solutions design different models for each task, and the output from the ATE model is used as the input to the APC model, which may result in error propagation among different steps because APC is affected by ATE error. These methods are impractical… More >

  • Open Access

    ARTICLE

    Syntax-Based Aspect Sentiment Quad Prediction by Dual Modules Neural Network for Chinese Comments

    Zhaoliang Wu1, Shanyu Tang2, Xiaoli Feng1, Jiajun Zou3, Fulian Yin1,4,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2873-2888, 2023, DOI:10.32604/cmc.2023.037060 - 31 March 2023

    Abstract Aspect-Based Sentiment Analysis (ABSA) is one of the essential research in the field of Natural Language Processing (NLP), of which Aspect Sentiment Quad Prediction (ASQP) is a novel and complete subtask. ASQP aims to accurately recognize the sentiment quad in the target sentence, which includes the aspect term, the aspect category, the corresponding opinion term, and the sentiment polarity of opinion. Nevertheless, existing approaches lack knowledge of the sentence’s syntax, so despite recent innovations in ASQP, it is poor for complex cyber comment processing. Also, most research has focused on processing English text, and ASQP… More >

  • Open Access

    ARTICLE

    The Nest of Torquigener Albomaculosus: Fluid-Dynamic Aspects and Potential for Bio-Inspired Engineering

    Zhimin Zhao1,2, Shangbin Wang1, Yuanhao Tie3, Ning Feng1,2,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.7, pp. 1837-1850, 2023, DOI:10.32604/fdmp.2023.026814 - 08 March 2023

    Abstract Torquigener albomaculosus, also known as the white-spotted pufferfish, is known for creating circular nests in the underwater sand as part of the mating ritual. The nests are built by the males to attract females through the nest’s impressive design and related ability to gather fine sand particles. As the fluid-dynamic processes associated with these unique nests are still almost completely unknown, in the present study, an analysis has been conducted to investigate how the geometric parameters related to the nest design influence the fluid velocity in its center. For this reason, a geometric model of More > Graphic Abstract

    The Nest of Torquigener Albomaculosus: Fluid-Dynamic Aspects and Potential for Bio-Inspired Engineering

  • Open Access

    ARTICLE

    Potential of Thai Bast Fibers for Injection Molded PLA Composites

    Nina Graupner1,*, Thiprada Poonsawat2, Koranat Narkpiban3,4, Jörg Müssig1

    Journal of Renewable Materials, Vol.11, No.5, pp. 2279-2300, 2023, DOI:10.32604/jrm.2023.025529 - 13 February 2023

    Abstract Thailand has a huge variability of bast fiber plants, some of which have been little researched regarding their applicability in composites. Bast fiber(bundle)s from different species were investigated and incorporated into a polylactide (PLA) matrix by injection molding. Hemp and kenaf were used as well-studied fibers, while roselle, Fryxell and paper mulberry are less extensively characterized. Tensile strength, tensile modulus and interfacial shear strength (IFSS) of single fiber(bundle)s were highest for hemp, followed by kenaf, roselle, Fryxell and paper mulberry. Despite the lower tensile strength and IFSS of paper mulberry, the highest tensile strength was… More > Graphic Abstract

    Potential of Thai Bast Fibers for Injection Molded PLA Composites

  • Open Access

    ARTICLE

    Aspect-Based Sentiment Analysis for Social Multimedia: A Hybrid Computational Framework

    Muhammad Rizwan Rashid Rana1,*, Saif Ur Rehman1, Asif Nawaz1, Tariq Ali1, Azhar Imran2, Abdulkareem Alzahrani3, Abdullah Almuhaimeed4,*

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2415-2428, 2023, DOI:10.32604/csse.2023.035149 - 09 February 2023

    Abstract People utilize microblogs and other social media platforms to express their thoughts and feelings regarding current events, public products and the latest affairs. People share their thoughts and feelings about various topics, including products, news, blogs, etc. In user reviews and tweets, sentiment analysis is used to discover opinions and feelings. Sentiment polarity is a term used to describe how sentiment is represented. Positive, neutral and negative are all examples of it. This area is still in its infancy and needs several critical upgrades. Slang and hidden emotions can detract from the accuracy of traditional… More >

  • Open Access

    ARTICLE

    Battle Royale Optimization with Fuzzy Deep Learning for Arabic Sentiment Classification

    Manar Ahmed Hamza1,*, Hala J. Alshahrani2, Jaber S. Alzahrani3, Heba Mohsen4, Mohamed I. Eldesouki5, Mohammed Rizwanullah1

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2619-2635, 2023, DOI:10.32604/csse.2023.034519 - 09 February 2023

    Abstract Aspect-Based Sentiment Analysis (ABSA) on Arabic corpus has become an active research topic in recent days. ABSA 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 text. Most of the prevailing Arabic ABSA techniques heavily depend upon dreary feature-engineering and pre-processing tasks and utilize external sources such as lexicons. In 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 tools.… More >

  • Open Access

    EDITORIAL

    Introduction to the Special Issue on Mathematical Aspects of Computational Biology and Bioinformatics

    Dumitru Baleanu1,2,*, Carla M. A. Pinto3, Sunil Kumar4

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 1-3, 2023, DOI:10.32604/cmes.2023.026471 - 05 January 2023

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Deep Learning for Depression Detection Using Twitter Data

    Doaa Sami Khafaga1, Maheshwari Auvdaiappan2, K. Deepa3, Mohamed Abouhawwash4,5, Faten Khalid Karim1,*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1301-1313, 2023, DOI:10.32604/iasc.2023.033360 - 05 January 2023

    Abstract Today social media became a communication line among people to share their happiness, sadness, and anger with their end-users. It is necessary to know people’s emotions are very important to identify depressed people from their messages. Early depression detection helps to save people’s lives and other dangerous mental diseases. There are many intelligent algorithms for predicting depression with high accuracy, but they lack the definition of such cases. Several machine learning methods help to identify depressed people. But the accuracy of existing methods was not satisfactory. To overcome this issue, the deep learning method is… More >

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