11. An apparatus, comprising: one or more processors; memory; and a program module, wherein the program module is stored in the memory and, during operation of the apparatus, is executed by the one or more processors to select a subset of a set of comments associated with a group of documents, the program module including: instructions for accessing, at memory locations in the memory, the set of comments and a predetermined annotation probability distribution of annotations for another set of comments associated with another group of documents, wherein the annotation probability distribution specifies biases in the annotations for the other set of comments; and instructions for selecting the subset based on the annotation probability distribution and an objective function from a supervised-learning technique, wherein the objective function is optimized by maximizing an expression comprising the annotation probability distribution and the objective function.
11. An apparatus, comprising: one or more processors; memory; and a program module, wherein the program module is stored in the memory and, during operation of the apparatus, is executed by the one or more processors to select a subset of a set of comments associated with a group of documents, the program module including: instructions for accessing, at memory locations in the memory, the set of comments and a predetermined annotation probability distribution of annotations for another set of comments associated with another group of documents, wherein the annotation probability distribution specifies biases in the annotations for the other set of comments; and instructions for selecting the subset based on the annotation probability distribution and an objective function from a supervised-learning technique, wherein the objective function is optimized by maximizing an expression comprising the annotation probability distribution and the objective function. 17. The apparatus of claim 11 , wherein the set of comments are currently unannotated.