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This book constitutes the refereed proceedings of the 10th International Conference on Extending Database Technology, EDBT 2006, held in Munich, Germany, in March 2006. The 60 revised research papers presented together with eight industrial application papers, 20 software demos, and three invited contributions were carefully reviewed and selected from 352 submissions. The papers are organized in topical sections.
This book occupies a unique position in the field of statistical analysis in the behavioural and social sciences in that it targets learners who would benefit from learning more conceptually and less computationally about statistical procedures and the software packages that can be used to implement them. This book provides a comprehensive overview of this important research skill domain with an emphasis on visual support for learning and better understanding. The primary focus is on fundamental concepts, procedures and interpretations of statistical analyses within a single broad illustrative research context. The book covers a wide range of descriptive, correlational and inferential statistical procedures as well as more advanced procedures not typically covered in introductory and intermediate statistical texts. It is an ideal reference for postgraduate students as well as for researchers seeking to broaden their conceptual exposure to what is possible in statistical analysis.
The refereed proceedings of the 8th International Symposium on Spatial and Temporal Databases, SSTD 2003, held at Santorini Island, Greece in July 2003. The 28 revised full papers presented together with a keynote paper were carefully reviewed and selected from 105 submissions. The papers are organized in topical sections on access methods, advanced query processing, data mining and data warehousing, distance-based queries, mobility and moving points management, modeling and languages, similarity processing, systems and implementation issues.
This book enriches unsupervised outlier detection research by proposing several new distance-based and density-based outlier scores in a k-nearest neighbors’ setting. The respective chapters highlight the latest developments in k-nearest neighbor-based outlier detection research and cover such topics as our present understanding of unsupervised outlier detection in general; distance-based and density-based outlier detection in particular; and the applications of the latest findings to boundary point detection and novel object detection. The book also offers a new perspective on bridging the gap between k-nearest neighbor-based outlier detection and clustering-based outlier detection, laying the groundwork for future advances in unsupervised outlier detection research. The authors hope the algorithms and applications proposed here will serve as valuable resources for outlier detection researchers for years to come.