1. A system for determining a relevancy ranking score, comprising: a processor; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to: receive a query including one or more constraints, wherein one of the one or more constraints includes an operator; receive a search result based on the query; and determine the relevancy ranking score for the received search result based at least in part on the operator associated with the one or more constraints of the query, wherein the relevancy ranking score is determined based at least in part on a feature score multiplied by a weight associated with the feature score, wherein the feature score comprises a scope/depth score, and wherein the scope/depth score comprises a score indicating satisfied constraints, wherein the scope/depth score comprises: determining whether any attribute has contains-like constraints; and wherein if no attribute has contains-like constraints, then scope/depth score=a constant value; wherein if attributes have contains-like constraints, then 
 scope/depth score=Σ( nbCT total[attribute]*Weight[attribute]* Score[attribute])/Σ( nbCT total[attribute]*Weight[attribute]); where: Σ: sum for all attributes; nbCTtotal[attribute] is the number of contains-like constraints for the attribute counting up to a maximum of constraints; Weight[attribute] is the weight factor for a specific attribute; and 
 Score[attribute]=( nbCT ok[attribute]+bonus Occ )/ nbCT total[attribute]* F scope( nbCT total[attribute]); where: nbCTok[attribute] is the number of satisfied contains-like constraints for a specific attribute, counting up to a maximum of number satisfied constraints; bonusOcc is added in the event that the contains-like constraint value occurs multiple times; and Fscope(x) is a function that takes a number of constraints as parameter.