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  • Open Access

    ARTICLE

    Leveraging User-Generated Comments and Fused BiLSTM Models to Detect and Predict Issues with Mobile Apps

    Wael M. S. Yafooz*, Abdullah Alsaeedi

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 735-759, 2024, DOI:10.32604/cmc.2024.048270

    Abstract In the last decade, technical advancements and faster Internet speeds have also led to an increasing number of mobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobile apps. The use of these apps eases our daily lives, and all customers who need any type of service can access it easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digital services to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services, particularly during two large occasions, Umrah and Hajj. However, pilgrims… More >

  • Open Access

    ARTICLE

    Quality Prediction of Wearable Apps in the Google Play Store

    Shifa Siddiqui1, Muhammad Shahzad Faisal1, Shahzada Khurram2, Azeem Irshad3, Mohammed Baz4, Habib Hamam5, Naeem Iqbal6, Muhammad Shafiq7,*

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 877-892, 2022, DOI:10.32604/iasc.2022.022266

    Abstract Play Store reviews play an important role in demonstrating that decisions are made from the user’s perspective, and contain a wealth of knowledge that can be used to understand quality issues and help developers build higher-quality mobile applications. Even for very important information, it can ensure the authenticity of user-generated content. In Play Store, wearable applications were recently launched, and are always open and easy to use, and are gradually being welcomed by users. Driven by popularity and self-interest, profit-incentive developers are developing low-quality applications and hiring robots to exaggerate ratings, reviews, or install counts. This is how spam in… More >

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