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Please provide a detail explanation of this incremental mining:
Suppose that we have an existing transaction database TDB for which we have already mined the frequent patterns. Also we have a new set of transaction ΔTDB that we are adding to TDB.
Given a ?xed min-support threshold, σ (e.g., σ=0.5%), present in plain language the steps for an efficient incremental mining algorithm that can maximally use the previously mined information when a new set of transactions ΔTDB is added to the existing transaction database TDB.
Hint: An itemset is frequent in TDB+ΔTDB, it must be frequent in at least one of them. Also some itemsets will become frequent because of the combined count.
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