1. A system for optimizing computer-based crowd-sourced polling, comprising: a processor; and a memory comprising instructions that, when executed by the processor, cause the processor to perform a method comprising: receiving an input query representing a crowd-sourced poll comprising two or more branches, each branch associated with a corresponding set of worker qualifications, the query being formatted as a multi-layer structure; iteratively reducing the multi-layer structure of the input query to construct a reformulated query, the reformulated query having a reduced complexity relative to the input query; reducing one or more of expected completion time and expected cost associated with the reformulated query by matching the reformulated query to an optimized execution process selected from a plurality of predefined execution processes; presenting the reformulated query and matching optimized execution process as an optimized version of the crowd-sourced poll for execution via a computer-based crowd-sourcing backend; during execution of the optimized version of the crowd-sourced poll, improving poll efficiency by automatically changing the matching optimized execution process to another of the predefined execution processes and dynamically changing the reformulated query to correspond to the automatically changed execution process in response to collected runtime statistics relating to execution of the optimized version of the crowd-sourced poll; and further during execution, presenting the changed reformulated query and changed matching optimized execution process for continued execution via the computer-based crowd-sourcing backend.
1. A system for optimizing computer-based crowd-sourced polling, comprising: a processor; and a memory comprising instructions that, when executed by the processor, cause the processor to perform a method comprising: receiving an input query representing a crowd-sourced poll comprising two or more branches, each branch associated with a corresponding set of worker qualifications, the query being formatted as a multi-layer structure; iteratively reducing the multi-layer structure of the input query to construct a reformulated query, the reformulated query having a reduced complexity relative to the input query; reducing one or more of expected completion time and expected cost associated with the reformulated query by matching the reformulated query to an optimized execution process selected from a plurality of predefined execution processes; presenting the reformulated query and matching optimized execution process as an optimized version of the crowd-sourced poll for execution via a computer-based crowd-sourcing backend; during execution of the optimized version of the crowd-sourced poll, improving poll efficiency by automatically changing the matching optimized execution process to another of the predefined execution processes and dynamically changing the reformulated query to correspond to the automatically changed execution process in response to collected runtime statistics relating to execution of the optimized version of the crowd-sourced poll; and further during execution, presenting the changed reformulated query and changed matching optimized execution process for continued execution via the computer-based crowd-sourcing backend. 5. The system of claim 1 wherein matching the reformulated query to an optimized execution process selected from a plurality of predefined execution processes further comprises post-filtering available crowd-sourced workers to include crowd-sourced workers matching qualifying questions extracted from the input query.