DocumentCode
1957417
Title
Patterns in large numerical data
Author
Lin, Tsau Young
Author_Institution
Dept. of Comput. Sci., San Jose State Univ., CA, USA
fYear
2002
fDate
2002
Firstpage
306
Lastpage
309
Abstract
For time series data, the interest is in "vertical" patterns, not "horizontal" associations; in other words, the focus is on patterns of a large (long) numerical sequence (of vectors or numbers). This paper is theoretical; all data has no noise. It searches for several important mathematical concepts in data mining, such as pattern and prediction and the notion of large. It proposes that data is large if the complexity of data is more than the complexity of the pattern, and reconfirms the previous proposal that a pattern\´s complexity should be smaller than data complexity.
Keywords
data mining; database theory; sequences; time series; very large databases; complexity; data mining; large numerical data; numbers; patterns; prediction; time series data; vectors; Algebra; Automation; Binary sequences; Computer science; Data mining; Databases; Information theory; Machine learning; Mathematics; Polynomials;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society, 2002. Proceedings. NAFIPS. 2002 Annual Meeting of the North American
Print_ISBN
0-7803-7461-4
Type
conf
DOI
10.1109/NAFIPS.2002.1018075
Filename
1018075
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