官方网站:http://www.journals.elsevier.com/data-and-knowledge-engineering/
投稿网址:https://www.evise.com/evise/faces/pages/login/login.jspx?resourceUrl=%2Ffaces%2Fpages%2Fnavigation%2FNavController.jspx%3FJRNL_ACR%3DDATAK%26
atabase 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.
数据库系统和知识库系统有许多共同的原则。数据与知识工程(DKE)促进了这两个相关领域之间的思想交流和互动。DKE吸引了世界各地的研究人员、设计师、管理人员和用户。期刊的主要目标是识别、调查和分析设计和有效使用这些系统的基本原则。DKE通过发布有关数据工程、知识工程和这两个领域的接口的原始研究成果、技术进展和新闻项目来实现这一目标。DKE涵盖以下主题:1、数据和知识的表示和操作:概念数据模型。知识表示技术。数据/知识操作语言和技术。2、数据库、专家或基于知识的系统的体系结构:数据库/知识库/专家系统的新体系结构、设计和实现技术、语言和用户界面、分布式体系结构。3、数据/知识库的构建:数据/知识库设计方法和工具、数据/知识获取方法、完整性/安全性/维护问题。4、应用、案例研究和管理问题:数据管理问题、知识工程实践、办公室和工程应用。5、使用基于语言学或人机界面原理的工具指定和开发数据和知识库的工具。6、在网络空间中实施、设计和使用KBS涉及的通信方面。加上…会议报告、活动日程、书评等。
大类学科 | 分区 | 小类学科 | 分区 | Top期刊 | 综述期刊 |
计算机科学 | 4区 | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机:人工智能 COMPUTER SCIENCE, INFORMATION SYSTEMS 计算机:信息系统 | 4区 4区 | 否 | 否 |
JCR分区等级 | JCR所属学科 | 分区 | 影响因子 |
Q4 | COMPUTER SCIENCE, INFORMATION SYSTEMS | Q4 | 1.5 |
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Q4 |
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