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Annals of Data Science (AODS)

Publisher :

Springer Science and Business Media Deutschland GmbH

Scopus Profile
Peer reviewed only
Scopus Profile
Open Access
  • Business
  • Computer Science
e-ISSN :

2198-5812

Issue Frequency :

Bi-Monthly

p-ISSN :

2198-5804

Est. Year :

2014

Mobile :

4962213450

Country :

Germany

Language:

English

APC :

YES

Email :

journalpermissions@springernature.com

Journal Descriptions

Annals of Data Science is a scholarly journal focusing on Big Data analytics and applications. Publishes a broad range of research findings, experimental results, and case studies in data science. Promotes interdisciplinary techniques, including statistics, artificial intelligence, and optimization for Big Data processing and data mining. Encourages application of knowledge derived from Big Data in real-life scenarios. Focuses on semi-structured and unstructured data analysis, Big Data modeling, and Big Data mining. Annals of Data Science (AODS) publishes cutting-edge research findings, experimental results and case studies of data science. Although data science is regarded as an interdisciplinary field of using mathematics, statistics, databases, data mining, high-performance computing, knowledge management and virtualization to discover knowledge from big data, it should have its own scientific contents, such as axioms, laws and rules, which are fundamentally important for experts in different fields to explore their own interests from big data. AODS encourages contributors to address such challenging problems at this exchange platform. At present, how to discover knowledge from heterogeneous data under big data environment, intelligent algorithm research, computing power networks as well as the digital economy problems needs to be addressed. AODS is a series of volumes edited by either the editorial office or guest editors. Guest editors will be responsible for call-for-papers and the review process for high-quality contributions in their volumes.


Annals of Data Science (AODS) is :

International, Peer-Reviewed, Open Access, Refereed, Business, Computer Science , Online or Print, Bi-Monthly Journal

UGC Approved, ISSN Approved: P-ISSN - 2198-5804, E-ISSN - 2198-5812, Established in - 2014, Impact Factor

Not Provide Crossref DOI

Indexed in Scopus

Not indexed in WoS, DOAJ, PubMed, UGC CARE

Indexing

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Google Scholar
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Publications of AODS

Research Article
  • dott image March, 2018

Reliability Estimation in Load-Sharing System Model with Application to Real Data

This study deals with the reliability analysis of a multi-component load sharing system where failure of any component within the system induces higher failure rate on the remaining survivin...

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