Springer » International Journal of Data Science and Analytics
Springer » International Journal of Data Science and Analytics
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Data Science has been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social sci­ence, and lifestyle.
A common-specific feature cross-fusion attention mechanism for KGVQA
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Enhancing the Vietoris–Rips simplicial complex for topological data analysis: applications in cancer gene expression datasets
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Predicting the pharmaceutical needs of hospitals using machine learning algorithms
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Building the interpolating model for interval time series based on the fuzzy clustering technique
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CfP: Learning from Temporal Data
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Guest Editors: João Mendes-Moreira, Joydeep Chandra, Albert Bifet ..read more
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CfP: Innovative Hardware and Architectures for Ubiquitous Data Science
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Guest Editors: Dr. Faheem Khan, Dr. Umme Laila, Dr. Muhammad Adnan Khan ..read more
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CfP: CCF BigData conference Journal Track on ‘Data Science in China’
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Guest Editors: Dr. Faheem Khan, Dr. Umme Laila, Dr. Muhammad Adnan Khan ..read more
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CfP: Theoretical and Practical Data Science and Analytics 
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A probabilistic spatio-temporal neural network to forecast COVID-19 counts
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Forecasting implied volatilities of currency options with machine learning techniques and econometrics models
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