AAAI Sponsored Journals — Data Mining and Knowledge Discovery Journal

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. KDD is concerned with issues of scalability, the multi-step knowledge discovery process for extracting useful patterns and models from raw data stores (including data cleaning and noise modelling), and issues of making discovered patterns understandable. Data Mining and Knowledge Discovery is intended to be the premier technical publication in the field, providing a resource collecting relevant common methods and techniques and a forum for unifying the diverse constituent research communities