14. A system, comprising: a memory; and one or more processors coupled to the memory, wherein the memory comprises program instructions executable by the one or more processors to implement a genetic rule generator configured to: generate a population of candidate rules for detecting duplicates, each duplicate representing different item description information entries that describe a common item, wherein each candidate rule comprises one or more independent rule conditions and one or more elements for each independent rule condition specifying how a portion of one set of item description information should be compared to another set of item description information for duplicate detection; for each candidate rule of the population, apply that rule to a reference data set including known duplicates and non-duplicates in order to determine a measure of that candidate rule's performance with respect to detecting duplicates; assign each candidate rule a fitness score based on the respective performance measurement for that candidate rule, wherein the fitness score of a given candidate rule is representative of that candidate rule's probability of being selected as a parent for a new generation of candidate rules; based on the fitness scores, select a subset of the population of candidate rules as parents for the new generation of candidate rules; change one or more elements of one or more rule conditions of one or more of the parent candidate rules to generate the new generation of candidate rules; and select from the new generation of candidate rules or one or more subsequent generations of candidate rules, one or more rules for inclusion within a rule set for detecting duplicates within item description information.
14. A system, comprising: a memory; and one or more processors coupled to the memory, wherein the memory comprises program instructions executable by the one or more processors to implement a genetic rule generator configured to: generate a population of candidate rules for detecting duplicates, each duplicate representing different item description information entries that describe a common item, wherein each candidate rule comprises one or more independent rule conditions and one or more elements for each independent rule condition specifying how a portion of one set of item description information should be compared to another set of item description information for duplicate detection; for each candidate rule of the population, apply that rule to a reference data set including known duplicates and non-duplicates in order to determine a measure of that candidate rule's performance with respect to detecting duplicates; assign each candidate rule a fitness score based on the respective performance measurement for that candidate rule, wherein the fitness score of a given candidate rule is representative of that candidate rule's probability of being selected as a parent for a new generation of candidate rules; based on the fitness scores, select a subset of the population of candidate rules as parents for the new generation of candidate rules; change one or more elements of one or more rule conditions of one or more of the parent candidate rules to generate the new generation of candidate rules; and select from the new generation of candidate rules or one or more subsequent generations of candidate rules, one or more rules for inclusion within a rule set for detecting duplicates within item description information. 22. The system of claim 14 , wherein the genetic rule generator is configured to generate said one or more subsequent generations, wherein said generating comprises repeating said applying, said assigning, said selecting a subset, and said performing in order to generate the one or more subsequent generations.