16. A system for feature selection for ranking, comprising: a processor; a memory coupled to the processor, wherein the processor is configured for: processing data to select features from an entire feature set; assigning an importance score to the features, wherein the importance score includes ranking performance; defining a similarity score between the features based on the ranking performance, wherein the similarity score is based on a correlation between ranking results of the two features; using an algorithm to maximize cumulative importance score and minimize mutual similarity score of the features, the algorithm includes: constructing an undirected graph and using a node to represent a feature; representing a weight of the node and a weight of an edge between two nodes; and constructing a set to contain the selected features; and identifying the features that are selected for ranking, wherein the features that are selected have a largest cumulative importance score and a least mutual similarity score.
17. The system of claim 16 , wherein the identifying the features comprises selecting the features that maximize total importance scores of the selected features and minimize total similarity scores between the selected features, wherein the features selected for ranking models an optimization problem.