Data Mining and Knowledge Discovery

期刊简介：Advances in data gathering, storage, and distribution have created a need for computational tools and techniques to aid in data analysis. Data Mining and Knowledge Discovery in Databases (KDD) is a rapidly growing area of research and application that builds on techniques and theories from many fields, including statistics, databases, pattern recognition and learning, data visualization, uncertainty modelling, data warehousing and OLAP, optimization, and high performance computing.

【译文】数据收集、存储和分布的进步，产生了对辅助数据分析的计算工具和技术需求。数据挖掘和数据库中的知识发现（KDD）是一个快速发展的研究领域和应用领域，它建立在多个领域的技巧和理论之上，包括统计学、数据库、模式识别和学习、数据可视化、不确定性建模、数据仓库和OLAP、优化以及高性能计算。