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International Journal of Data Science and Analytics


International Journal of Data Science and Analytics OnlineFirst articles

18-06-2022 | Regular Paper

Sample-selection-adjusted random forests

A predictive model that is trained with non-randomly selected samples can offer biased predictions for the population. This paper discusses when non-random selection is a problem. For the applications in which it is a problem, this paper presents …

17-06-2022 | Editorial

Collective intelligence and knowledge exploration: an introduction

Collective intelligence and Knowledge Exploration (CI and KE) have been adopted to solve many problems. They are particularly used by companies as a support for innovation to efficiently obtain usable results. CI is usually defined as a group …

14-06-2022 | Regular Paper

Data-driven analytics of COVID-19 ‘infodemic’

The rampant of COVID-19 infodemic has almost been simultaneous with the outbreak of the pandemic. Many concerted efforts are made to mitigate its negative effect to information credibility and data legitimacy. Existing work mainly focuses on …

10-06-2022 | Review

A survey on event and subevent detection from microblog data towards crisis management

Social media data analysis is a popular research domain since the last decade. Detecting the events and sub-events from social media posts that require special attention is one of the key research problem in this domain with wide range of …

06-06-2022 | Regular Paper

Exo-SIR: an epidemiological model to analyze the impact of exogenous spread of infection

Epidemics like Covid-19 and Ebola have impacted people’s lives significantly. The impact of mobility of people across the countries or states in the spread of epidemics has been significant. The spread of disease due to factors local to the …

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About this journal

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.

International Journal of Data Science and Analytics
Volume 1/2016 - Volume 14/2022
Springer International Publishing
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