1. A computer-implemented method, comprising: generating a set of seed rules comprising: one or more rules resulting from one or more previously performed machine learning operations that were previously performed in regard to a set of item description entries, and one or more randomly or pseudo-randomly generated rules; performing one or more machine learning operations on the set of seed rules to generate a set of duplicate detection rules for determining whether a given pair of item description entries is a duplicate pair, wherein a given duplicate pair represents different item description entries that describe a common item, wherein said performing the one or more machine learning operations on the set of seed rules is performed in regard to another set of item description entries, wherein the other set of item description entries includes one or more differences from the set of item description entries in regard to which the one or more previously performed machine learning operations were previously performed; and applying the set of duplicate detection rules to multiple item description entries to identify at least one duplicate pair of item description entries.
1. A computer-implemented method, comprising: generating a set of seed rules comprising: one or more rules resulting from one or more previously performed machine learning operations that were previously performed in regard to a set of item description entries, and one or more randomly or pseudo-randomly generated rules; performing one or more machine learning operations on the set of seed rules to generate a set of duplicate detection rules for determining whether a given pair of item description entries is a duplicate pair, wherein a given duplicate pair represents different item description entries that describe a common item, wherein said performing the one or more machine learning operations on the set of seed rules is performed in regard to another set of item description entries, wherein the other set of item description entries includes one or more differences from the set of item description entries in regard to which the one or more previously performed machine learning operations were previously performed; and applying the set of duplicate detection rules to multiple item description entries to identify at least one duplicate pair of item description entries. 2. The computer-implemented method of claim 1 , further comprising merging the at least one duplicate pair of item description entries into a single combined item description entry for the common item.