TAILIEUCHUNG - Appendix A: An Overview on Time Series Data Mining

Appendix A: An Overview on Time Series Data Mining includes Introduction, Similarity Search in Time Series Data, Feature-based Dimensionality Reduction, Discretization, Other Time Series Data Mining Tasks, Conclusions. | Appendix A: An Overview on Time Series Data Mining Duong Tuan Anh Faculty of Computer Science & Engineering Ho Chi Minh City University of Technology October 2009 Course: Decision Support Systems An Overview on Time series Data Mining Outline Introduction Similarity Search in Time Series Data Feature-based Dimensionality Reduction Discretization Other Time Series Data Mining Tasks Conclusions Introduction 0 50 100 150 200 250 300 350 400 450 500 23 24 25 26 27 28 29 A time series is a collection of observations made sequentially in time. Examples: Financial time series, scientific time series Time series Similarity Search Some examples: - Identifying companies with similar patterns of growth. - Determining products with similar selling patterns - Discovering stocks with similar movement in stock prices. - Finding out whether a musical score is similar to one of a set of copyrighted scores. Time series Similarity Search Distance Measures Euclidean distance Dynamic Time Warping Other distance measures Euclidean Distance Metric Given two time series Q = q1 qn and C = c1 cn their Euclidean distance is defined as: Q C D(Q,C) Fixed Time Axis Sequences are aligned “one to one”. “Warped” Time Axis Nonlinear alignments are possible. Dynamic Time Warping (Berndt et al.) Dynamic Time Warping is a technique that finds the optimal alignment between two time series if one time series may be “warped” non-linearly by stretching or shrinking it along its time axis. This warping between two time series can be used or to determine the similarity between the two time series. Dynamic Time Warping DTW facilitates the discovery of flexible patterns from time series. DTW is used in speech regcognition to determine if two waveforms represent the same spoken phrase. Disadvantage: .

• Cơ sở dữ liệu
• An Overview on Time Series Data Mining
• Similarity Search in Time Series Data
• Feature based Dimensionality Reduction
• Other Time Series Data Mining Tasks
• Data Mining
• Data warehousing and data mining
• Data warehousing
• Data warehouse modelling
• Data mining functionalities
• Association rule mining
• FP growth algorithm
• K Nearest neighbor classification
• Lecture Data mining
• Bài giảng Khai thác dữ liệu
• Data mining for data streams
• Mining data streams
• Stream frequent pattern analysis
• Khai phá dữ liệu
• Overview of data mining
• Association rules
• Other Data Mining problems
• Applications of data mining
• Sequence data
• Sequential pattern mining
• Sequential pattern mining algorithms
• Data stream mining
• Data stream processing algorithms
• Cash register model
• Time series model
• Lecture Data mining and analysis
• Khai thác dữ liệu
• Data analysis foundations
• Frequent pattern mining
• Itemset mining
• Sequence mining
• Graph pattern mining
• Data warehouses
• On line analytical processing
• Association rules mining
• Mining association rules
• Computational complexity
• Frequent itemset generation
• Mining frequent closed patterns
• Data warehouse
• Data warehouse architecture
• Data warehouse implementation
• Data warehouse—subject oriented
• Graph data
• High dimensional data
• Numeric attributes
• Categorical attributes
• Kernel methods
• Dimensionality reduction
• Summarizing itemsets
• Rule assessment