A processor is configured to process information according to attribute value criteria organized as a decision tree, wherein an attribute value criterion of the attribute value criteria is a range of attribute values, wherein a portion of the attribute value criteria lead to a matching target value among target values of the decision tree, wherein each of the target values, including the matching target value, is assigned a respective priority value, wherein the processor is configured to count, for each specific attribute value, a respective number of particular attribute value appearances in a set of rules and a respective number of attribute value matches comprising range based matches based on range based appearances for the each specific attribute value, wherein the processor determines the decision tree based on information entropy values and information gain values.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A network node comprising: a first interface for receiving incoming packets; a second interface for sending outgoing packets; and a processor configured to count each specific attribute value of a plurality of specific attribute values, a respective number of particular attribute value appearances in a set of rules and a respective number of attribute value matches comprising range based matches based on range based appearances, determine a decision tree based on information entropy values and information gain values, the information entropy values based on the count of the respective number of the particular attribute value appearances and the respective number of the attribute value matches, the decision tree leading to determination of target values, the target values used in the sending of the outgoing packets, and process the incoming packets according to attribute value criteria organized as the decision tree, an attribute value criterion of the attribute value criteria being a range of attribute values, wherein a portion of the attribute value criteria lead to a matching target value among the target values of the decision tree, wherein each of the target values, including the matching target value, is assigned a respective priority value. 2. The network node of claim 1 wherein the decision tree is an N-ary balanced tree. 3. The network node of claim 2 wherein a next branch in the decision tree is added at a location in the decision tree to maximize information gain. 4. The network node of claim 3 wherein the information gain is determined according to a difference of information entropy values. 5. The network node of claim 4 wherein the information entropy values are determined based on the respective number of the particular attribute value appearances in the set of rules and the respective number of the attribute value matches for the each specific attribute value. 6. The network node of claim 5 wherein the decision tree is arranged in order of decreasing information gain with increasing distance from a root of the decision tree. 7. The network node of claim 6 wherein the information entropy values are recalculated for remaining attribute value criteria not including a first information entropy value after a first attribute value criterion having the first information entropy value has been assigned to a preceding branch of the decision tree. 8. A method for routing packets in a network, the method comprising: counting, by a first processor, for each specific attribute value of a plurality of specific attribute values, a respective number of particular attribute value appearances in a set of rules and a respective number of attribute value matches comprising range based matches based on range based appearances; determining, by the first processor, a decision tree based on information entropy values and information gain values; receiving incoming packets at a first interface; processing the incoming packets by a second processor according to attribute value criteria organized as a decision tree, wherein an attribute value criterion of the attribute value criteria is a range of attribute values, wherein a portion of the attribute value criteria lead to a matching target value among target values of the decision tree, wherein each of the target values, including the matching target value, is assigned a respective priority value; and transmitting outgoing packets at a second interface based on the processing of the incoming packets by the second processor. 9. The method of claim 8 wherein the decision tree is an N-ary balanced tree. 10. The method of claim 9 further comprising: adding, by the first processor, a next branch in the decision tree at a location in the decision tree to maximize information gain. 11. The method of claim 10 further comprising: determining, by the first processor, the information gain according to a difference of information entropy values. 12. The method of claim 11 wherein the information entropy values are determined by the first processor based on the respective number of the particular attribute value appearances in the set of rules and the respective number of the attribute value matches for the each specific attribute value. 13. The method of claim 12 wherein the decision tree is arranged, by the first processor, in order of decreasing information gain with increasing distance from a root of the decision tree. 14. The method of claim 13 further comprising: recalculating, by the first processor, remaining information entropy values for remaining attribute value criteria not including a first information entropy value for a first attribute value criterion after the first attribute criterion having the first information entropy value has been assigned to a preceding branch of the decision tree. 15. An apparatus comprising: a memory; and a processor coupled to the memory, the processor configured to receive rules having rule attribute values, to store the rule attribute values in the memory, to count, for each specific attribute value of the rule attribute values, a respective number of particular attribute value appearances in the rules and a respective number of attribute value matches of each attribute value comprising range based matches based on range based appearances in the rules, the processor further configured to determine a decision tree based on information entropy values and information gain values, the information entropy values based on the count of the respective number of the particular attribute value appearances and the respective number of attribute value matches. 16. The apparatus of claim 15 wherein the decision tree is an N-ary balanced tree. 17. The apparatus of claim 16 wherein a next branch in the decision tree is added at a location in the decision tree to maximize information gain. 18. The apparatus of claim 17 wherein the information gain is determined according to a difference of information entropy values. 19. The apparatus of claim 18 wherein the information entropy values are determined based on the respective number of the particular attribute value appearances in the set of rules and the respective number of the attribute value matches for the each specific attribute value. 20. The apparatus of claim 19 wherein the decision tree is arranged in order of decreasing information gain with increasing distance from a root of the decision tree.