B. Xia. Similarity search in time series data sets. M. Sc. Thesis, Simon Fraser University, B.C., Canada, Dec. 1997. Home/Search Document Details and Download
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.... and adjustment of concept hierarchies [16] mining multi level association rules [15] meta rule guided mining of associations [22] incremental and distributed mining of associations [8, 7] constraint pushing in association mining [10, 27] mining periodicity and similarity in time series data [11, 30], multi level classification and prediction [23, 6] spatial data cube construction [21] spatial association rule mining [24] OLAP mining [12] Weblog mining [31] etc. A data mining system, DBMiner [16, 14] has been constructed with our years of research and development. The system integrates ....
.... are adopted in most previous analyses of similarity based time series [2] With the popular adoption of wavelet transformation and analysis methods, we examine the wavelet transformation based sim ilarity mining methods for discovery of trends and or similar curves or curve segments [30]. Template segments can be specified by users based on the given curve segments or using template primitives. Then wavelet transformation techniques can be used for curve smoothing and approximation, scaling, and translation, and then fragment based pattern matching analysis. Our study shows that ....
B. Xia. Similarity search in time series data sets. M. Sc. Thesis, Simon Fraser University, B.C., Canada, Dec. 1997.
Towards On-Line Analytical Mining in Large Databases *.. - Intelligent Database.. (Correct)
.... are adopted in most previous analyses of similarity based time series [2] With the popular adoption of wavelet transformation and analysis methods, we examine the wavelet transformation based sim ilarity mining methods for discovery of trends and or similar curves or curve segments [30]. Template segments can be specified by users based on the given curve segments or using template primitives. Then wavelet transformation techniques can be used for curve smoothing and approximation, scaling, and translation, and then fragment based pattern matching analysis. Our study shows that ....
B. Xia. Similarity search in time series data sets. M. Sc. Thesis, Simon Fraser University, B.C., Canada, Dec. 1997.
Towards On-Line Analytical Mining in Large Databases - Han (1998) (10 citations) (Correct)
.... and adjustment of concept hierarchies [16] mining multi level association rules [15] meta rule guided mining of associations [22] incremental and distributed mining of associations [8, 7] constraint pushing in association mining [10, 27] mining periodicity and similarity in time series data [11, 30], multi level classification and prediction [23, 6] spatial data cube construction [21] spatial association rule mining [24] OLAP mining [12] Weblog mining [31] etc. A data mining system, DBMiner [16, 14] has been constructed with our years of research and development. The system integrates ....
.... transformation, are adopted in most previous analyses of similarity based time series [2] With the popular adoption of wavelet transformation and analysis methods, we examine the wavelet transformation based similarity mining methods for discovery of trends and or similar curves or curve segments [30]. Template segments can be specified by users based on the given curve segments or using template primitives. Then wavelet transformation techniques can be used for curve smoothing and approximation, scaling, and translation, and then fragment based pattern matching analysis. Our study shows that ....
B. Xia. Similarity search in time series data sets. M.Sc. Thesis, Simon Fraser University, B.C., Canada, Dec. 1997.
Periodic Pattern Search on Time-Related Data Sets - Gong (1997) (5 citations) (Correct)
....series obtained are rarely noise free. Special signal smoothing techniques need be applied to preprocessing these time series so that the resulting time series we work on are relatively simple and smooth. A method using wavelet transform technique to generalize an input signal is being studied in [40], which may provide us with an efficient tool to handle this problem. Another issue of concern is the accuracy relaxation aspect missing in the arbitrary periodicity search problem. As stated in Section 5.1.4, accuracy relaxation problem requires special handling of the input sequence that will ....
B. Xia. Similarity Search in Time Series Data Sets. In Master thesis, Simon Fraser University, 1997.
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