1. A computer-implemented method of mining address data to locate a preferred address for each of a plurality of parcels, comprising: maintaining a package-level detail database of active shipment records in associated memory, each active shipment record comprising an active tracking number, an active ship-to address, and an active delivery pattern code; maintaining an electronic archive of delivery records in said memory, each delivery record comprising a past tracking number, a past ship-to address, a past delivery pattern code, and a stop identifier; receiving address indicia associated with a current parcel; assigning a mining key to said current parcel, said mining key comprising a parcel tracking number and a current delivery pattern code related to said address indicia; comparing said mining key to said package-level detail database and said archive by having one or more computer components execute logic for: (a) retrieving from said archive those select delivery records having a past delivery pattern code that matches said current delivery pattern code, each of said select delivery records having a select past ship-to address; (b) retrieving from said package-level detail database those select active shipment records having an active ship-to address that matches any said select past ship-to address in said select delivery records; building a set of mined data comprising said select delivery records and said select active shipment records; prioritizing said set of mined data in order of the records most closely associated with said mining key, such that a preferred address related to said mining key occurs first, wherein said step of prioritizing said set of mined data comprises having at least one of said one or more computer components execute logic for: (a) replacing one or more sequence values in a plurality of ship-to address records having the same stop identifier; (b) clustering together those said ship-to address records having the same delivery pattern code; (c) building a delivery pattern similarity matrix by counting the coincidence of each delivery pattern code and each ship-to address within said set of mined data; (d) summing the overlapping delivery pattern occurrences within said delivery pattern similarity matrix for each pair of ship-to addresses; (e) building a stop identifier similarity matrix by counting the coincidence of each stop identifier and each ship-to address within said set of mined data; (f) summing the overlapping stop occurrences within said stop identifier similarity matrix for each pair of ship-to addresses; and (g) sorting said set of mined data in order of the highest number of overlapping delivery pattern occurrences and the highest number of overlapping stop occurrences; and assigning said preferred address to said current parcel for delivery.