Systems, methods, and non-transitory computer-readable media can acquire information associated with a set of rules and a set of activities identified by the set of rules as being potentially illegitimate. A priority order for a set of properties associated with the set of rules can be acquired. The set of rules can be ranked based on the priority order. A highest ranked rule can be stored into a record. The highest ranked rule can be removed from consideration out of the set of rules. At least one activity, identified by the highest ranked rule, can be removed from consideration out of the set of activities. In some instances, the record can be provided.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer-implemented method comprising: acquiring, by a computing system, information associated with a set of rules and a set of activities identified by the set of rules as being potentially illegitimate; acquiring, by the computing system, a priority order for a set of properties associated with the set of rules; ranking, by the computing system, the set of rules based on the priority order; storing, by the computing system, a highest ranked rule into a record; removing from consideration, by the computing system, the highest ranked rule out of the set of rules; removing from consideration, by the computing system, at least one activity, identified by the highest ranked rule, out of the set of activities; and providing, by the computing system, the record. 2. The computer-implemented method of claim 1, wherein the removing of the highest ranked rule out of the set of rules produces a subset of rules, and wherein the removing of the at least one activity out of the set of activities produces a subset of activities. 3. The computer-implemented method of claim 2, further comprising: ranking the subset of rules based on the priority order; storing a next highest ranked rule into the record as a next entry; removing from consideration the next highest ranked rule out of the subset of rules; and removing from consideration at least one activity, identified by the next highest ranked rule, out of the subset of activities. 4. The computer-implemented method of claim 3, wherein the ranking of the subset of rules, the storing of the next highest ranked rule into the record, the removing of the next highest ranked rule out of the subset of rules, and the removing of the at least one activity out of the subset of activities are performed repeatedly until no rules are left in the subset of rules. 5. The computer-implemented method of claim 4, wherein the ranking of the subset of rules, the storing of the next highest ranked rule into the record, the removing of the next highest ranked rule out of the subset of rules, and the removing of the at least one activity out of the subset of activities are performed prior to the providing of the record. 6. The computer-implemented method of claim 1, wherein the providing of the record corresponds to at least one of presenting at least a portion of data included in the record, generating a report based on the at least the portion of data included in the record, or transmitting a communication based on the at least the portion of the data included in the record. 7. The computer-implemented method of claim 1, wherein the acquiring of the priority order is based on at least one of a user instruction, a system instruction, or a defined setting. 8. The computer-implemented method of claim 1, wherein the set of properties includes at least a first property and a second property, and wherein the priority order prioritizes the first property over the second property. 9. The computer-implemented method of claim 8, wherein the ranking of the set of rules further comprises: ranking the set of rules based on the first property; and ranking at least some rules in the set of rules based on the second property when the at least some rules are tied with respect to the first property. 10. The computer-implemented method of claim 1, wherein the set of properties includes at least one of a respective precision by amount value associated with each rule in the set of rules, a respective true positive amount value associated with each rule in the set of rules, a respective precision by event value associated with each rule in the set of rules, a respective true positive event value associated with each rule in the set of rules, or a respective identifier associated with each rule in the set of rules. 11. The computer-implemented method of claim 1, further comprising: defining threshold criteria for retaining rules; determining that at least one rule in the record satisfies the threshold criteria for retaining rules; and implementing the at least one rule to identify potentially illegitimate activities. 12. The computer-implemented method of claim 11, wherein the threshold criteria for retaining rules is satisfied when the at least one rule is associated with a benefit that outweighs a cost associated with the at least one rule. 13. The computer-implemented method of claim 11, further comprising: deprecating one or more rules in the record that fail to satisfy the threshold criteria for retaining rules. 14. The computer-implemented method of claim 1, wherein the record includes at least one of a list, a sequence, an order, or a group. 15. The computer-implemented method of claim 1, wherein the set of activities is identified by the set of rules as being potentially illegitimate based on historical data. 16. The computer-implemented method of claim 15, wherein one or more activities in the set of activities correspond to one or more fraudulent transactions occurring in a networked environment. 17. The computer-implemented method of claim 15, wherein the set of activities is identified by the set of rules as being potentially illegitimate based on applying one or more machine learning techniques to the historical data. 18. The computer-implemented method of claim 17, wherein the one or more machine learning techniques are associated with at least one of an information gain technique, a classification technique, a clustering technique, a decision tree classifier technique, a decision tree learning technique, a random forest technique, a logistic regression technique, a linear regression technique, or a gradient boosting technique. 19. A system comprising: at least one processor; and a memory storing instructions that, when executed by the at least one processor, cause the system to perform: acquiring information associated with a set of rules and a set of activities identified by the set of rules as being potentially illegitimate; acquiring a priority order for a set of properties associated with the set of rules; ranking the set of rules based on the priority order; storing a highest ranked rule into a record; removing from consideration the highest ranked rule out of the set of rules; removing from consideration at least one activity, identified by the highest ranked rule, out of the set of activities; and providing the record. 20. A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of a computing system, cause the computing system to perform: acquiring information associated with a set of rules and a set of activities identified by the set of rules as being potentially illegitimate; acquiring a priority order for a set of properties associated with the set of rules; ranking the set of rules based on the priority order; storing a highest ranked rule into a record; removing from consideration the highest ranked rule out of the set of rules; removing from consideration at least one activity, identified by the highest ranked rule, out of the set of activities; and providing the record.