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Data & Knowledge Engineering (DKE)

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インパクトファクター:
2.6
出版社:
Elsevier
ISSN:
0169-023X
閲覧:
32386
フォロー:
50

論文募集

Data & Knowledge Engineering (DKE) is an academic journal published by Elsevier. (ISSN 0169-023X, impact factor 2.6, CCF B).

Database Systems and Knowledgebase Systems share many common principles. Data & Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these two related fields of interest. DKE reaches a world-wide audience of researchers, designers, managers and users. The major aim of the journal is to identify, investigate and analyze the underlying principles in the design and effective use of these systems. DKE achieves this aim by publishing original research results, technical advances and news items concerning data engineering, knowledge engineering, and the interface of these two fields. DKE covers the following topics: 1. Representation and Manipulation of Data & Knowledge: Conceptual data models. Knowledge representation techniques. Data/knowledge manipulation languages and techniques. 2. Architectures of database, expert, or knowledge-based systems: New architectures for database / knowledge base / expert systems, design and implementation techniques, languages and user interfaces, distributed architectures. 3. Construction of data/knowledge bases: Data / knowledge base design methodologies and tools, data/knowledge acquisition methods, integrity/security/maintenance issues. 4. Applications, case studies, and management issues: Data administration issues, knowledge engineering practice, office and engineering applications. 5. Tools for specifying and developing Data and Knowledge Bases using tools based on Linguistics or Human Machine Interface principles. 6. Communication aspects involved in implementing, designing and using KBSs in Cyberspace. Plus... conference reports, calendar of events, book reviews etc.
最終更新：Dou Sun（）

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