Machine Learning in E-services

Machine learning is a discipline within computer science that went through massive growth in the past several years. Through a series of mathematical algorithms, together with the increasing availability of data and computational power, a machine learning system can make accurate predictions based on existing data. In addition to the development of new algorithms or the fine-tuning of existing ones, many researchers identified a huge potential in the application of machine learning methods to solve relevant problems. One of the most promising application fields is ‘e-services’, that is, the provision of traditional services through an online Internet-based channel.

This Special Issue will address the most recent advances in the introduction of machine learning techniques to improve and personalize e-services. Thus, contributions are expected to present original research on machine learning with real-world applications in e-services.

Topics for this Special Issue include, but are not limited to the following:

• New machine learning algorithms for e-services.
• Benchmarking of machine learning alternatives in e-services.
• Adaptation and fine-tuning of machine learning in specific e-services domains.
• Machine learning in e-learning.
• Machine learning in e-health.
• Machine learning in e-government.
• Machine learning in e-commerce.
• Machine learning in e-Business.
• Machine learning in e-security.
• Machine learning in social networks.
• Machine learning in marketing.
• Machine learning for the development and deployment of e-services on cloud computing scenarios.

Prof. Dr. Luís E. Anido-Rifon
Dr. Sonia Valladares Rodriguez
Guest Editors

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