The present design is directed to a series of interconnected compute servers including a supervisory hardware node and a plurality of knowledge hardware nodes, wherein the series of interconnected compute servers are configured to categorize and scale performance of multiple disjoint algorithms across a seemingly infinite actor population, wherein the series of interconnected compute servers are configured to normalize data using a common taxonomy, distribute normalized data relatively evenly across the plurality of knowledge hardware nodes, supervise algorithm execution across knowledge hardware nodes, and collate and present results of analysis of the seemingly infinite actor population.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A system comprising: a series of interconnected compute servers comprising a supervisory hardware node and a plurality of knowledge hardware nodes, wherein the series of interconnected compute servers are configured to categorize and scale performance of multiple disjoint algorithms across a seemingly infinite actor population, wherein the series of interconnected compute servers are configured to: normalize data using a common taxonomy; distribute normalized data relatively evenly across the plurality of knowledge hardware nodes; supervise algorithm execution across knowledge hardware nodes; and collate and present results of analysis of the seemingly infinite actor population. 2. The system of claim 1, wherein at least one knowledge hardware node comprises a relevancy engine comprising: a rule package; and a series of processors organized in a tree arrangement and configured to perform functions according to a rule set contained in the rule package; wherein the topmost processor in the tree structure provides results of analysis using fuzzy logic; wherein the rule package comprises set comprises a series of rule sets, each rule set corresponding to a different one of the series of processors. 3. The system of claim 1, wherein the plurality of knowledge hardware nodes comprise processor nodes and aggregator nodes, and a first set of the knowledge hardware nodes performs computations and provides results of the computations to one aggregator node. 4. The system of claim 1, wherein the rule package comprises is a hardware container including a collection of rules organized logically or thematically. 5. The system of claim 1, wherein each rule set comprises rules from a rules storage device and an event described in a corresponding data model. 6. The system of claim 5, wherein the corresponding data model defines a type of event, event organization, and characteristics of each data field in the event. 7. The system of claim 1, wherein the rule set comprises a relevancy rule that generates a compatibility index measuring degree to which an associated premise is true. 8. The system of claim 3, wherein each processor node comprises an effect assessment contribution set by collection of rules in an associated rule set comprising an average of compatibility index values for at least one rule. 9. The system of claim 3, wherein each processor node has a relevant weighting representing a weight the node is to be accorded by its aggregator node. 10. A system comprising: a knowledge base system comprising a rule package comprising a plurality of rule sets; and a relevancy processor arrangement comprising a series of processors organized in a tree arrangement and configured to perform functions according to at least one of the plurality of rule sets contained in the rule package, wherein a topmost processor in the tree structure provides results of analysis using fuzzy logic, wherein the relevancy processor arrangement comprises a series of interconnected compute servers comprising aggregator hardware nodes and processor hardware nodes, wherein the series of interconnected compute servers are configured to categorize and scale performance of multiple disjoint algorithms across a seemingly infinite actor population; wherein the series of interconnected compute servers are configured to normalize data using a common taxonomy. 11. The system of claim 10, wherein the series of interconnected compute servers are further configured to distribute normalized data relatively evenly across the plurality of knowledge hardware nodes. 12. The system of claim 11, wherein the series of interconnected compute servers are further configured to supervise algorithm execution across knowledge hardware nodes. 13. The system of claim 12, wherein the series of interconnected compute servers are further configured to collate and present results of analysis of the seemingly infinite actor population. 14. The system of claim 10, wherein a first set of the knowledge hardware nodes performs computations and provides results of the computations to one aggregator node. 15. The system of claim 10, wherein the rule package comprises is a hardware container including a collection of rules organized logically or thematically. 16. The system of claim 10, wherein each rule set comprises rules from a rules storage device and an event described in a corresponding data model. 17. The system of claim 16, wherein the corresponding data model defines a type of event, event organization, and characteristics of each data field in the event. 18. The system of claim 10, wherein the rule set comprises a relevancy rule that generates a compatibility index measuring degree to which an associated premise is true. 19. A system comprising: a knowledge base hardware system comprising a rule package comprising a plurality of rule sets configured to receive rules from a rule device and events from an events device; and a relevancy processor arrangement comprising a series of processors organized in a tree arrangement and configured to perform functions according to at least one of the plurality of rule sets contained in the rule package using fuzzy logic, wherein the relevancy processor arrangement comprises a series of interconnected compute servers comprising aggregator hardware nodes and processor hardware nodes, wherein the series of interconnected compute servers are configured to categorize and scale performance of multiple disjoint algorithms across a seemingly infinite actor population. 20. The system of claim 19, wherein the series of interconnected compute servers are configured to normalize data using a common taxonomy, distribute normalized data relatively evenly across the plurality of knowledge hardware nodes, supervise algorithm execution across knowledge hardware nodes, and collate and present results of analysis of the seemingly infinite actor population.