Mobile Data Science and Intelligent Apps: Concepts, AI-Based Modeling and Research Directions
Artificial intelligence (AI) techniques have grown rapidly in recent years in the context of computing with smart mobile phones that typically allows the devices to function in an intelligent manner. Popular AI techniques include machine learning and deep learning methods, natural language processin...
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| Vydané v: | Mobile networks and applications Ročník 26; číslo 1; s. 285 - 303 |
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| Hlavní autori: | , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
New York
Springer US
01.02.2021
Springer Nature B.V |
| Predmet: | |
| ISSN: | 1383-469X, 1572-8153, 1572-8153 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | Artificial intelligence (AI) techniques have grown rapidly in recent years in the context of computing with smart mobile phones that typically allows the devices to function in an intelligent manner. Popular AI techniques include machine learning and deep learning methods, natural language processing, as well as knowledge representation and expert systems, can be used to make the target mobile applications intelligent and more effective. In this paper, we present a comprehensive view on “
mobile data science and intelligent apps”
in terms of
concepts
and
AI-based modeling that
can be used to design and develop intelligent mobile applications for the betterment of human life in their diverse day-to-day situation. This study also includes the concepts and insights of various
AI-powered intelligent apps
in several application domains, ranging from personalized recommendation to healthcare services, including COVID-19 pandemic management in recent days. Finally, we highlight several
research issues and future directions
relevant to our analysis in the area of mobile data science and intelligent apps. Overall, this paper aims to serve as a
reference point and guidelines
for the mobile application developers as well as the researchers in this domain, particularly from the technical point of view. |
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| Bibliografia: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ISSN: | 1383-469X 1572-8153 1572-8153 |
| DOI: | 10.1007/s11036-020-01650-z |