Online association rule mining
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Interactive sequence discovery by incremental mining
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Informatics and computer science intelligent systems applications
Classification rule mining for a stream of perennial objects
RuleML'2011 Proceedings of the 5th international conference on Rule-based reasoning, programming, and applications
| Hi-index | 0.00 |
We present a novel algorithm to compute large itemsets online. It needs at most 2 scans of the transaction sequence. During the first scan the user is free to change the support threshold. The algorithm maintains a superset of all large itemsets and a deterministic lower and upper bound on the support of each itemset. We continously display the resulting association rules along with an interval on the rule''s support and confidence. The algorithm can compute association rules for a transaction sequence which is read from a network and is too large to be stored locally for a rescan. During the second scan we determine the precise support for each large itemset and prune all small itemsets using a new forward-pruning technique.