《数据分析与知识发现》期刊征文

发布时间：2018-06-06 04:01

本文选题：知识发现 + 数据分析　；参考：《数据分析与知识发现》2017年06期

【摘要】：正1期刊定位《数据分析与知识发现》聚焦各行各业中以大数据为基础、依靠复杂挖掘分析、进行知识发现与预测、支持决策分析和政策制定的研究与应用,致力于提供理论指导、技术支持和最佳实践。期刊依靠并融汇计算机科学、科学计量学、社会计量学、网络计量学、数据科学、管理科学、预测分析、循证政策分析等领域,帮助人们从数据发现知识、从知识提炼智慧(洞察力)、从知识和智慧推演并设计解决方案,并且嵌入到知识密集和知识驱动的各行各业流程管理和决策支持。2征稿范围期刊广泛吸纳计算机科学、数据科学、情报科学以及数字科研、数字教育和数字文化等领域的技术与方法,研究数据驱动的语义计算、内容分析、数据挖掘、知识发现、智能管理和决策支持等方面的技术、方法、系统以及支撑设施、政策与机制等,尤其是聚焦从海量、异构、分布、动态、甚至富媒体数据中挖掘和发现知识以支持研究、管理和决策的理论、方法和技术。主题领域包括:
[Abstract]:"data Analysis and knowledge Discovery" focuses on the research and application of decision analysis and policy making, which is based on big data, relies on complex mining and analysis, and supports the research and application of decision analysis and policy making. Committed to providing theoretical guidance, technical support and best practices. Journals rely on and integrate computer science, scientific metrology, social metrology, web-based metrology, data science, management science, predictive analysis, evidence-based policy analysis, and other fields to help people discover knowledge from data. From knowledge extraction wisdom (insight), from knowledge and wisdom to extrapolate and design solutions, and to embed knowledge-intensive and knowledge-driven industry processes management and decision support. 2 journals extensively incorporate computer science Technologies and methods in the fields of data science, information science and digital research, digital education and digital culture, research on data-driven semantic computing, content analysis, data mining, knowledge discovery, Technologies, methods, systems, and supporting facilities, policies and mechanisms for intelligent management and decision support, especially focusing on mining and discovering knowledge from massive, heterogeneous, distributed, dynamic, and even rich media data to support research, Theory, methods and techniques of management and decision making. Thematic areas include:
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