  CrowdPlanner -- a novel crowd-based route recommendation system has been
developed, which requests human workers to evaluate candidates routes
recommended by different sources and methods, and determine the best route
based on the feedbacks of these workers. Our system addresses two critical
issues in its core components: a) task generation component generates a series
of informative and concise questions with optimized ordering for a given
candidate route set so that workers feel comfortable and easy to answer; and b)
worker selection component utilizes a set of selection criteria and an
efficient algorithm to find the most eligible workers to answer the questions
with high accuracy.
