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Crowdsourcing harnesses human effort to solve computer-hard problems such as photo tagging, entity resolution and sentiment analysis. Such tasks often have different levels of difficulty and workers have varying levels of skill at completing them. With a limited budget, it is important to wisely allocate the spend among the tasks and workers such that the overall outcome is as good as possible. Most existing work addresses this budget allocation problem by assuming that workers have a single level of ability for all tasks and each task involves a choice between just two alternatives. However, this neglects the fact that many crowdsourcing applications ask workers to choose between multiple alternatives and that different tasks can belong to a variety of diverse categories. Moreover, workers may have varying abilities across these categories. For example, a science enthusiast is likely to do better than a cinephile …