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provides a venue for papers on machine learning featuring new algorithms with empirical, theoretical, psychological, or biological justification; experimental and/or theoretical studies yielding new insights into the design and behavior of learning in intelligent systems; accounts of applications of existing techniques that shed light on the strengths and weaknesses of the methods; formalization of new learning tasks (e.g., in the context of new applications) and of methods for assessing performance on those tasks; development of new analytical frameworks that advance theoretical studies of practical-learning methods; computational models of data from natural learning systems at the behavioral or neural level; or extremely well-written surveys of existing work.

7. ACM Transactions on Knowledge Discovery from Data (TKDD)

http://tkdd.cs.uiuc.edu/index.html

The ACM TKDD addresses a full range of research in the knowledge discovery and analysis of diverse forms of data. Such subjects include scalable and effective algorithms for data mining and data warehousing, mining data streams, mining multimedia data, mining high-dimensional data, mining text, Web, and semi-structured data, mining spatial and temporal data, data mining for community generation, social-network analysis, and graph structured data, security and privacy issues in data mining, visual, interactive and online data mining, preprocessing and postprocessing for data mining, robust and scalable statistical methods, data-mining languages, foundations of data mining, KDD framework and process, and novel applications and infrastructures exploiting data-mining technology.

8. Journal of Intelligent Information Systems (JIIS)

http://www.springerlink.com/content/0925-9902

The JIIS: Integrating Artificial Intelligence and Database Technologies fosters and presents research and development results focused on the integration of AI and database technologies to create next generation information systems—intelligent information systems. JIIS provides a forum wherein academics, researchers, and practitioners may publish high-quality, original and state-of-the-art papers describing theoretical aspects, systems architectures, analysis and design tools and techniques, and implementation experiences in intelligent information systems. Articles published in JIIS include research papers, invited papers, meeting, workshop and conference announcements and reports, survey and tutorial articles, and book reviews. Topics include foundations and principles of data, information, and knowledge models; and methodologies for IIS analysis, design, implementation, validation, maintenance and evolution.

9. Statistical Analysis and Data Mining

http://www.amstat.org/publications/sadm.cfm

The Statistical Analysis and Data Mining addresses the broad area of data analysis, including data-mining algorithms, statistical approaches, and practical applications. Topics include problems involving massive and complex data sets, solutions using innovative data-mining algorithms and/or novel statistical approaches, and the objective evaluation of analyses and solutions. Of special interest are articles that describe analytical techniques and discuss their application to real problems in such a way that they are accessible and beneficial to domain experts across science, engineering, and commerce.

10. Intelligent Data Analysis

http://www.iospress.nl/html/1088467x.php

Intelligent Data Analysis provides a forum for the examination of issues related to the research and applications of AI techniques in data analysis across a variety of disciplines. These techniques include (but are not limited to) all areas of data visualization, data preprocessing (fusion, editing, transformation, filtering, sampling), data engineering, database mining techniques, tools and applications, use of domain knowledge in data analysis, evolutionary algorithms, machine learning, neural nets, fuzzy logic, statistical pattern recognition, knowledge filtering, and postprocessing. In particular, we prefer papers that discuss development