18. A cloud-based crowd-sourced query system, comprising: a general purpose computing device; and a computer program comprising program modules executable by the computing device, wherein the computing device is directed by the program modules of the computer program to: receive a crowd-sourced query comprising two or more branches, each branch associated with a corresponding set of worker qualifications; apply one or more automated optimizations to the crowd-sourced query to construct a reformulated query, the reformulated query having a reduced complexity relative to the crowd-sourced query; reduce one or more of expected completion time and expected cost associated with the reformulated query by associating the reformulated query with a matching optimized execution process selected from a plurality of predefined execution processes; provide the reformulated query and matching optimized execution process as an optimized version of the crowd-sourced query for execution via a cloud-based crowd-sourcing backend; during execution of the optimized version of the crowd-sourced query, improve query efficiency by automatically changing the matching optimized execution process to a different one of the predefined execution processes and dynamically changing the reformulated query to correspond to the changed execution process in response to collected runtime statistics relating to execution of the optimized version of the crowd-sourced query; and further during execution, presenting the changed reformulated query and changed matching optimized execution process for continued execution via the cloud-based crowd-sourcing backend.
20. The cloud-based crowd-sourced query system of claim 18 wherein matching the reformulated query to an optimized execution process further comprises selecting one or more execution processes from a plurality of predefined execution processes, the plurality of predefined execution processes comprising: post-filtering available crowd-sourced workers to include crowd-sourced workers matching qualifying questions extracted from the crowd-sourced query; inviting a first set of crowd-sourced workers that match qualifying questions extracted from the crowd-sourced query to respond to the reformulated query; and inviting a second set of crowd-sourced workers that match predetermined qualifications determined via one or more multiple choice questions to respond to the reformulated query.