Abstract: A reputation system to evaluate work is disclosed. Answer data for each of one or more unsupervised workers is received. The answer data includes one or more answers each representing a judgment by the worker that reflects on the quality of a given work product. The reputation system determines programmatically, based at least in part on a reputation data of an owner of the work product, the answer data, and a respective reputation data of the respective unsupervised workers, which answers are correct.

Abstract: Using a distributed set of unsupervised workers to produce a work product is disclosed. In some embodiments, a work product is received. A review task to review the work product is provided to a reviewing worker included in the set of unsupervised workers. A result of the review task is received. A determination is made, based at least in part on the review result, whether the work product satisfies an acceptance criteria.

Abstract: A method and apparatus to use a statistical model to classify electronic communications is disclosed. In one embodiment, an incoming electronic communication is analyzed in view of a preformulated statistical model to determine whether the communication is to be classified within at least one predetermined category. In one embodiment, the statistical model includes a set of features relating to an electronic communication.

Abstract: A method and apparatus to provide an improved statistical model is disclosed. In one embodiment a statistical model for an electronic communication media is generated. The statistical model based on a predetermined set of features of the electronic communication. The statistical model is thereafter processed with a genetic algorithm (GA) to generate a revised statistical mode. In one embodiment, the revised statistical model is provided in a classifier to classify incoming electronic communications. In one embodiment, the classifier is to determine whether a received electronic communication is to be classified as spam or legitimate.