Pattern: Difference between revisions
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New page: {{Quotation|Pattern is an expression in some language describing a subset of the data or a model applicable to the subset.|[Fayyad et al., 1996]}} == References == *[Fayyad et al., 1... |
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{{Quotation|[[Pattern]] is an expression in some language describing a subset of the data or a model applicable to the subset.|[Fayyad et al., 1996]}} | {{Quotation|[[Pattern]] is an expression in some language describing a subset of the data or a model applicable to the subset.|[Fayyad et al., 1996]}} | ||
{{Quotation|A '''pattern''' is made of recurring events or objects that repeat in a predictable manner. The most basic patterns are based on repetition and periodicity.|[Bertini and Lalanne, 2009]}} | |||
see [[Knowledge Discovery]] for an explanation of the relationship between [[Data]], [[Information]], [[Insight]], [[Model]], [[Pattern]], [[Hypothesis]], [[Knowledge]] and [[Knowledge Crystallization]]. | |||
== References == | == References == | ||
*[Bertini and Lalanne, 2009] Bertini, E. and Lalanne, D. 2009. [http://doi.acm.org/10.1145/1562849.1562851 Surveying the complementary role of automatic data analysis and visualization in knowledge discovery]. In Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery: integrating Automated Analysis with interactive Exploration (Paris, France, July 28 - 28, 2009). VAKD '09. ACM, New York, NY, 12-20 | |||
*[Fayyad et al., 1996] U. Fayyad, G. P.-Shapiro, and P. Smyth. From data mining to knowledge discovery in databases. AI Magazine, 17(3):37-54, Fall 1996. http://citeseer.ist.psu.edu/fayyad96from.html | |||
[[Category:Glossary]] | [[Category:Glossary]] |
Latest revision as of 10:47, 21 August 2009
Pattern is an expression in some language describing a subset of the data or a model applicable to the subset.
[Fayyad et al., 1996]
A pattern is made of recurring events or objects that repeat in a predictable manner. The most basic patterns are based on repetition and periodicity.
[Bertini and Lalanne, 2009]
see Knowledge Discovery for an explanation of the relationship between Data, Information, Insight, Model, Pattern, Hypothesis, Knowledge and Knowledge Crystallization.
References
- [Bertini and Lalanne, 2009] Bertini, E. and Lalanne, D. 2009. Surveying the complementary role of automatic data analysis and visualization in knowledge discovery. In Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery: integrating Automated Analysis with interactive Exploration (Paris, France, July 28 - 28, 2009). VAKD '09. ACM, New York, NY, 12-20
- [Fayyad et al., 1996] U. Fayyad, G. P.-Shapiro, and P. Smyth. From data mining to knowledge discovery in databases. AI Magazine, 17(3):37-54, Fall 1996. http://citeseer.ist.psu.edu/fayyad96from.html