This paper describes the platformisation of the mobile services domain,which in recent years has become a successful strategy for some hardware manufacturers and software companies.While having different platform stra...This paper describes the platformisation of the mobile services domain,which in recent years has become a successful strategy for some hardware manufacturers and software companies.While having different platform strategies and business models,they have succeeded in creating a demand for mobile software and content with end-users.This paper proposes a way to determine the optimum platform-charging mode that an operator should adopt to play a meaningful role in the mobile service domain and with respect to content with end-users.Four charging modes employed by mobile application stores are studied in this paper,namely the one-sided paid-by-users charging mode,the one-sided paid-by-advertisers charging mode,the two-sided differential paid charging mode and the two-sided paid and free access charging mode.Furthermore,a comparative analysis of the four modes is also presented.展开更多
In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mo...In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices 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 encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user comments.However, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long Short-TermMemory (LSTM), and Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.61071077
文摘This paper describes the platformisation of the mobile services domain,which in recent years has become a successful strategy for some hardware manufacturers and software companies.While having different platform strategies and business models,they have succeeded in creating a demand for mobile software and content with end-users.This paper proposes a way to determine the optimum platform-charging mode that an operator should adopt to play a meaningful role in the mobile service domain and with respect to content with end-users.Four charging modes employed by mobile application stores are studied in this paper,namely the one-sided paid-by-users charging mode,the one-sided paid-by-advertisers charging mode,the two-sided differential paid charging mode and the two-sided paid and free access charging mode.Furthermore,a comparative analysis of the four modes is also presented.
文摘In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices 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 encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user comments.However, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long Short-TermMemory (LSTM), and Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.
