Fuzzy Frequent Item Set Mining based on Recursive Elimination
نویسندگان
چکیده
Real life transaction data often miss some occurrences of items that are actually present. As a consequence some potentially interesting frequent item sets cannot be discovered, since with exact matching the number of supporting transactions may be smaller than the user-specified minimum. In order to allow approximate matching during the mining process, we propose an approach based on transaction editing. Our recursive algorithm relies on a step by step elimination of items from the transaction database together with a recursive processing of transaction subsets. This algorithm works without complicated data structures and allows us to find fuzzy frequent item sets easily.
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