Abstract: A computer-implemented method is provided of finding one or more data items that match one or more defined criteria in a dataset. The method comprises identifying data snippets of the dataset using a set of one or more attention rules; categorizing the identified data snippets using fuzzy matching by assigning them to buckets such that each bucket contains data snippets that are similar to another according to a similarity measure; classifying buckets containing data snippets having more than a threshold number of the true positive data items as true positive buckets and remaining buckets as false positive buckets; calculating culling rules based on the true positive buckets and the false positive buckets, and using the culling rules to remove the false positive data items from the true positive buckets.

Abstract: A computer-implemented method is provided of finding one or more data items that match one or more defined criteria in a dataset. The method comprises identifying data snippets of the dataset using a set of one or more attention rules; categorizing the identified data snippets using fuzzy matching by assigning them to buckets such that each bucket contains data snippets that are similar to another according to a similarity measure; classifying buckets containing data snippets having more than a threshold number of the true positive data items as true positive buckets and remaining buckets as false positive buckets; calculating culling rules based on the true positive buckets and the false positive buckets, and using the culling rules to remove the false positive data items from the true positive buckets.