1. A method for providing a search recommendation, the method comprising: training a relevance classifier, wherein the relevance classifier comprises a decision tree comprising a plurality of nodes and wherein training the relevance classifier comprises: receiving a plurality of log data associated with users' behavior, wherein each of the plurality of log data comprises a relevance factor and a feedback category comprising at least one of the following categories: accepted, explored, and rejected, for each of the plurality of log data, determining whether the associated relevance factor is associated with a node of a decision tree, in response to determining that the associated relevance factor is not associated with a node of the decision tree, create a new decision node associated with the relevance factor, in response to determining that the associated relevance factor is associated with a node of the decision tree, for each of the plurality of log data, updating a feedback category count associated with a decision node with the relevance factor of the log data according to the feedback category of the log data, and for each of the plurality of decision nodes, assigning a confidence value according to the feedback category count of the decision node; receiving a search query from a user; providing a plurality of search results to the user; capturing a behavior associated with the user and at least one of the plurality of search results; classifying a relevance for the at least one of the plurality of search results according to the captured behavior, wherein the captured behavior comprises at least one of the relevance factors associated with the relevance classifier; determining, according to the relevance classified for the at least one of the plurality of search results, whether the at least one of the plurality of search results comprises a potential best-bet search result; in response to determining that the at least one of the plurality of search results comprises the potential best-bet search result, determining whether the confidence value associated with the at least one of the relevance factors is greater than a threshold value; and in response to determining that the confidence value associated with the at least one of the relevance factors is greater than the threshold value adding the at least one of the plurality of search results to a store comprising recommended search results.
1. A method for providing a search recommendation, the method comprising: training a relevance classifier, wherein the relevance classifier comprises a decision tree comprising a plurality of nodes and wherein training the relevance classifier comprises: receiving a plurality of log data associated with users' behavior, wherein each of the plurality of log data comprises a relevance factor and a feedback category comprising at least one of the following categories: accepted, explored, and rejected, for each of the plurality of log data, determining whether the associated relevance factor is associated with a node of a decision tree, in response to determining that the associated relevance factor is not associated with a node of the decision tree, create a new decision node associated with the relevance factor, in response to determining that the associated relevance factor is associated with a node of the decision tree, for each of the plurality of log data, updating a feedback category count associated with a decision node with the relevance factor of the log data according to the feedback category of the log data, and for each of the plurality of decision nodes, assigning a confidence value according to the feedback category count of the decision node; receiving a search query from a user; providing a plurality of search results to the user; capturing a behavior associated with the user and at least one of the plurality of search results; classifying a relevance for the at least one of the plurality of search results according to the captured behavior, wherein the captured behavior comprises at least one of the relevance factors associated with the relevance classifier; determining, according to the relevance classified for the at least one of the plurality of search results, whether the at least one of the plurality of search results comprises a potential best-bet search result; in response to determining that the at least one of the plurality of search results comprises the potential best-bet search result, determining whether the confidence value associated with the at least one of the relevance factors is greater than a threshold value; and in response to determining that the confidence value associated with the at least one of the relevance factors is greater than the threshold value adding the at least one of the plurality of search results to a store comprising recommended search results. 4. The method of claim 1 , further comprising evaluating a plurality of captured behaviors associated with the at least one of the plurality of search results.