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An incremental mining algorithm for maintaining sequential patterns using pre-large sequences
2011
Expert systems with applications
Mining useful information and helpful knowledge from large databases has evolved into an important research area in recent years. Among the classes of knowledge derived, finding sequential patterns in temporal transaction databases is very important since it can help model customer behavior. In the past, researchers usually assumed databases were static to simplify data-mining problems. In real-world applications, new transactions may be added into databases frequently. Designing an efficient
doi:10.1016/j.eswa.2010.12.008
fatcat:t737gvbrazhkfa55kje6zuvzzi