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  • Open Access

    ARTICLE

    Multilingual Sentiment Mining System to Prognosticate Governance

    Muhammad Shahid Bhatti1,*, Saman Azhar1, Abid Sohail1, Mohammad Hijji2, Hamna Ayemen1, Areesha Ramzan1

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 389-406, 2022, DOI:10.32604/cmc.2022.021384

    Abstract In the age of the internet, social media are connecting us all at the tip of our fingers. People are linkedthrough different social media. The social network, Twitter, allows people to tweet their thoughts on any particular event or a specific political body which provides us with a diverse range of political insights. This paper serves the purpose of text processing of a multilingual dataset including Urdu, English, and Roman Urdu. Explore machine learning solutions for sentiment analysis and train models, collect the data on government from Twitter, apply sentiment analysis, and provide a python More >

  • Open Access

    ARTICLE

    MELex: The Construction of Malay-English Sentiment Lexicon

    Nurul Husna Mahadzir1, Mohd Faizal Omar2, Mohd Nasrun Mohd Nawi3,*, Anas A. Salameh4, Kasmaruddin Che Hussin5, Abid Sohail6

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1789-1805, 2022, DOI:10.32604/cmc.2022.021131

    Abstract Currently, the sentiment analysis research in the Malaysian context lacks in terms of the availability of the sentiment lexicon. Thus, this issue is addressed in this paper in order to enhance the accuracy of sentiment analysis. In this study, a new lexicon for sentiment analysis is constructed. A detailed review of existing approaches has been conducted, and a new bilingual sentiment lexicon known as MELex (Malay-English Lexicon) has been generated. Constructing MELex involves three activities: seed words selection, polarity assignment, and synonym expansions. Our approach differs from previous works in that MELex can analyze text More >

  • Open Access

    ARTICLE

    Evaluating the Impacts of Security-Durability Characteristic: Data Science Perspective

    Abdullah Alharbi1, Masood Ahmad2, Wael Alosaimi1, Hashem Alyami3, Alka Agrawal2, Rajeev Kumar4,*, Abdul Wahid5, Raees Ahmad Khan2

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 557-567, 2022, DOI:10.32604/csse.2022.020843

    Abstract Security has always been a vital research topic since the birth of web application. A great deal of research has been conducted to determine the ways of identifying and classifying security issues or goals However, in the recent years, it has been noticed that high secure web applications have less durability; thus reducing their business continuity. High security features of a web application are worthless unless they provide effective services to the user and meet the standards of commercial viability. Hence, there is a need to bridge the gap between security and durability of the… More >

  • Open Access

    ARTICLE

    Artificial Intelligence Based Optimal Functional Link Neural Network for Financial Data Science

    Anwer Mustafa Hilal1, Hadeel Alsolai2, Fahd N. Al-Wesabi3, Mohammed Abdullah Al-Hagery4, Manar Ahmed Hamza1,*, Mesfer Al Duhayyim5

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6289-6304, 2022, DOI:10.32604/cmc.2022.021522

    Abstract In present digital era, data science techniques exploit artificial intelligence (AI) techniques who start and run small and medium-sized enterprises (SMEs) to have an impact and develop their businesses. Data science integrates the conventions of econometrics with the technological elements of data science. It make use of machine learning (ML), predictive and prescriptive analytics to effectively understand financial data and solve related problems. Smart technologies for SMEs enable allows the firm to get smarter with their processes and offers efficient operations. At the same time, it is needed to develop an effective tool which can… More >

  • Open Access

    ARTICLE

    Towards Machine Learning Based Intrusion Detection in IoT Networks

    Nahida Islam1, Fahiba Farhin1, Ishrat Sultana1, M. Shamim Kaiser1, Md. Sazzadur Rahman1, Mufti Mahmud2, A. S. M. Sanwar Hosen3, Gi Hwan Cho3,*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1801-1821, 2021, DOI:10.32604/cmc.2021.018466

    Abstract The Internet of Things (IoT) integrates billions of self-organized and heterogeneous smart nodes that communicate with each other without human intervention. In recent years, IoT based systems have been used in improving the experience in many applications including healthcare, agriculture, supply chain, education, transportation and traffic monitoring, utility services etc. However, node heterogeneity raised security concern which is one of the most complicated issues on the IoT. Implementing security measures, including encryption, access control, and authentication for the IoT devices are ineffective in achieving security. In this paper, we identified various types of IoT threats… More >

  • Open Access

    ARTICLE

    Semantic Modeling of Events Using Linked Open Data

    Sehrish Jamil1, Salma Noor1,*, Iftikhar Ahmed2, Neelam Gohar1, Fouzia1

    Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 511-524, 2021, DOI:10.32604/iasc.2021.017770

    Abstract Significant happenings in terms of spatio-temporal factors are called events. In the digital age, these events and their associated features are scattered in various databases on the Internet. The event data are in heterogeneous formats, which are often not machine-readable. This leads to a lack of unification of event-related knowledge across different domains and results in a research gap in terms of event modeling and representation. Specialized event models are needed to overcome this gap and integrate relevant information of different similar events occurring worldwide. Our research explores the problem of heterogeneity in specialized event… More >

  • Open Access

    ARTICLE

    Competency Driven Resource Evaluation Method for Business Process Intelligence

    Abid Sohail1,*, Dhanapal Durai Dominic2, Mohammad Hijji3, Muhammad Arif Butt4

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1141-1157, 2021, DOI:10.32604/cmc.2021.018023

    Abstract Enterprises are continuously aiming at improving the execution of processes to achieve a competitive edge. One of the established ways of improving process performance is to assign the most appropriate resources to each task of the process. However, evaluations of business process improvement approaches have established that a method that can guide decision-makers to identify the most appropriate resources for a task of process improvement in a structured way, is missing. It is because the relationship between resources and tasks is less understood and advancement in business process intelligence is also ignored. To address this More >

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