Outlier detection for high dimensional data
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Some algorithms for data table (re)ordering using monotone systems
AIKED'06 Proceedings of the 5th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases
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The paradigm shift from hypothesis-driven to data-driven exploratory data analysis methods has been gaining acceptance in several emerging research areas as self-organization, machine learning, data mining and bioinformatics. In this paper, a compact overview of such data-driven method is given with short discussion about some properties and implementation issues and an implementation with structured query language is presented. One could make use of database capabilities, thereby leveraging on more than a decade of effort spent in making these systems robust, portable, scalable and concurrent.