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International Journal of Data Engineering (IJDE)
full name / name of organization:
Computer Science Journals
Data Engineering refers to the use of data engineering techniques and methodologies in the design, development and assessment of computer systems for different computing platforms and application environments. With the proliferation of the different forms of data and its rich semantics, the need for sophisticated techniques has resulted an in-depth content processing, engineering analysis, indexing, learning, mining, searching, management, and retrieval of data.
International Journal of Data Engineering (IJDE) is a peer reviewed scientific journal for sharing and exchanging research and results to problems encountered in today’s data engineering societies. IJDE especially encourage submissions that make efforts (1) to expose practitioners to the most recent research results, tools, and practices in data engineering topics; (2) to raise awareness in the research community of the data engineering problems that arise in practice; (3) to promote the exchange of data & information engineering technologies and experiences among researchers and practitioners; and (4) to identify new issues and directions for future research and development in the data & information engineering fields. IJDE is a peer review journal that targets researchers and practitioners working on data engineering and data management.
To build its International reputation, we are disseminating the publication information through Google Books, Google Scholar, Directory of Open Access Journals (DOAJ), Open J Gate, ScientificCommons, Docstoc and many more. Our International Editors are working on establishing ISI listing and a good impact factor for IJDE.
IJDE List of Topics
The realm of International Journal of Data Engineering (IJDE) extends, but not limited, to the following:
• Approximation and Uncertainty in Databases and Pro