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Mining frequent patterns is to discover the groups of items appearing always together excess of a user specified threshold from a large transaction database. However, the transactions will grow rapidly, such that the frequent itemsets may be changed due to the addition of the new transactions. The users may eager for getting the latest frequent itemsets from the updated database as soon as possible...
Mining frequent patterns refers to the discovery of the sets of items that frequently appear in a transaction database. Many approaches have been proposed for mining frequent itemsets from a large database, but a large number of frequent itemsets may be discovered. In order to present users fewer but more important patterns, researchers are interested in discovering frequent closed itemsets which...
Mining frequent itemsets is to discover the groups of items appearing always together excess of a user specified threshold from a transaction database. However, there may be many frequent itemsets existing in a transaction database, such that it is difficult to make a decision for a decision maker. Recently, mining frequent closed itemsets becomes a major research issue, since all frequent itemsets...
Mining frequent itemsets is an important research task for knowledge discovery, which is to discover the groups of items appearing always together excess of a user specified threshold from a transaction database. However, there may be many frequent itemsets existing in a transaction database, such that it is difficult to make a decision for a decision maker. Recently, mining frequent closed itemsets...
Mining frequent patterns is an important task for knowledge discovery, which discovers the groups of items appearing always together excess of a user specified threshold. A famous algorithm for mining frequent patterns is FP-Growth which constructs a structure called FP-tree and recursively mines frequent patterns from this structure by building conditional FP-trees. However, It is costly to recursively...
Many approaches have been proposed for mining frequent pattern. However, either the search space or memory space is huge, such that the performance for the previous approach degrades when the database is massive or the threshold for mining frequent patterns is low. In this paper, we propose an algorithm for mining frequent patterns. Our algorithm only needs to construct a FP-tree and traverse each...
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