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Efficient Algorithms for Mining High Utility Itemsets from Transactional Databases.

, , , and . IEEE Trans. Knowl. Data Eng., 25 (8): 1772-1786 (2013)

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Mining High Utility Mobile Sequential Patterns in Mobile Commerce Environments., , , and . DASFAA (1), volume 6587 of Lecture Notes in Computer Science, page 224-238. Springer, (2011)Online mining of temporal maximal utility itemsets from data streams., , and . SAC, page 1622-1626. ACM, (2010)Efficient algorithms for discovering high utility user behavior patterns in mobile commerce environments., , and . Knowl. Inf. Syst., 37 (2): 363-387 (2013)Efficient algorithms for mining maximal high utility itemsets from data streams with different models., , and . Expert Syst. Appl., 39 (17): 12947-12960 (2012)Discovering Valuable User Behavior Patterns in Mobile Commerce Environments., , , and . PAKDD Workshops, volume 7104 of Lecture Notes in Computer Science, page 77-88. Springer, (2011)Mining Sequential Patterns with Pattern Constraint., , , and . ACIIDS (1), volume 9011 of Lecture Notes in Computer Science, page 603-613. Springer, (2015)Mining interesting user behavior patterns in mobile commerce environments., , and . Appl. Intell., 38 (3): 418-435 (2013)UP-Growth: an efficient algorithm for high utility itemset mining., , , and . KDD, page 253-262. ACM, (2010)A One-Phase Method for Mining High Utility Mobile Sequential Patterns in Mobile Commerce Environments., , , and . IEA/AIE, volume 7345 of Lecture Notes in Computer Science, page 616-626. Springer, (2012)Mining top-K high utility itemsets., , , and . KDD, page 78-86. ACM, (2012)