International Journal of Data Science and Analytics
Data-driven scientific discovery is a key emerging paradigm driving research innovation and industrial development in domains such as business, social science, the Internet of Things, and cloud computing. The field encompasses the larger areas of data analytics, machine learning, and managing big data, while related new scientific challenges range from data capture, creation, storage, search, sharing, analysis, and visualization, to integration across heterogeneous, interdependent complex resources for real-time decision-making, collaboration, and value creation. The journal welcomes experimental and theoretical findings on data science and advanced analytics along with their applications to real-life situations.
Houtao Deng (July 2018)
A characterization of sample selection bias in system evaluation and the case of information retrieval
Massimo Melucci (July 2018)
- Journal Title
- International Journal of Data Science and Analytics
- Volume 1 / 2016 - Volume 5 / 2018
- Print ISSN
- Online ISSN
- Springer International Publishing
- Additional Links
- Industry Sectors
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