In my research field, Average Precision (for each query) and Mean Average Precision (for all queries) are the most widely used. They reflect both precision and recall information.
If we can regard the "retrieval" method as a solution of "recognition", we can also use ROC curve and/or AUC as the measure. They also reflect both precision and recall information.
Other measures include discounted cumulative gain, mean reciprocal rank, etc., but I never saw any people really used them in their studies (at least in my research field).