Efficient Discovery of Frequent Approximate Sequential Patterns

• Main Authors: ZHU, Feida, YAN, Xifeng, HAN, Jiawei, YU, Philip S.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2007
• Subjects: Hamming distance model; approximate sequential patterns; break-down-and-build-up methodology; frequent approximate sequential patterns; global search; incremental growth; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/933; https://ink.library.smu.edu.sg/context/sis_research/article/1932/viewcontent/EfficientDiscoveryFrequentAppSeqPatterns_2007.pdf
• Institution: Singapore Management University

We propose an efficient algorithm for mining frequent approximate sequential patterns under the Hamming distance model. Our algorithm gains its efficiency by adopting a "break-down-and-build-up" methodology. The "breakdown" is based on the observation that all occurrences of a fr...