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Data & Knowledge Engineering

From Wikipedia, the free encyclopedia
Academic journal
Data & Knowledge Engineering
Discipline Computer science
LanguageEnglish
Edited byP.P. Chen
Publication details
History1985–present
Publisher
Frequency Monthly
1.992 (2020)
Standard abbreviations
ISO 4 (alt· Bluebook (alt)
NLM (alt· MathSciNet (alt Paid subscription required)
ISO 4 Data Knowl. Eng.
Indexing
CODEN (alt · alt2· JSTOR (alt· LCCN (alt)
MIAR · NLM (alt· Scopus · W&L
CODEN DKENEW
ISSN 0169-023X  (print)
1872-6933 (web)
LCCN 90649274
OCLC no.630595125
Links

Data & Knowledge Engineering is a monthly peer-reviewed academic journal in the area of database systems and knowledge base systems. It is published by Elsevier and was established in 1985. The editor-in-chief is P.P. Chen (Louisiana State University).

Abstracting and indexing

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The journal is abstracted and indexed in Current Contents/Engineering, Computing & Technology,[1] Ei Compendex,[2] Inspec,[3] Science Citation Index Expanded,[1] Scopus,[4] and Zentralblatt MATH.[5] According to the Journal Citation Reports , the journal has a 2020 impact factor of 1.992.[6]

References

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  1. ^ a b "Master Journal List". Intellectual Property & Science. Clarivate Analytics. Archived from the original on 2017年09月26日. Retrieved 2017年02月14日.
  2. ^ "Content/Database Overview - Compendex Source List". Engineering Village. Elsevier . Retrieved 2017年02月14日.
  3. ^ "Inspec list of journals" (PDF). Inspec. Institution of Engineering and Technology . Retrieved 2017年02月14日.
  4. ^ "Source details: Data and Knowledge Engineering". Scopus preview. Elsevier . Retrieved 2017年02月14日.
  5. ^ "Serials Database". Zentralblatt MATH . Springer Science+Business Media. Archived from the original on 2017年11月07日. Retrieved 2017年02月14日.
  6. ^ "Data & Knowledge Engineering". 2020 Journal Citation Reports. Web of Science (Science ed.). Thomson Reuters. 2021.
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