Crowd-sourcing user participant recruitment method based on geo-social network

Abstract

Crowd-sourcing is a way of spreading tasks to different executive groups to solve a large number of tasks with group power. How to quickly collect a large number of executors is one of the main research problems of Crowd-sourcing task distribution. In this paper, a social network-oriented crowd-sourcing task information propagation method is adopted, which applies mobile behavior preference and information interaction among users to the task distribution process of swarm perception, accelerates the task information propagation process, and realizes more accurate and efficient task recommendation and assignment. Thesis research contents: one is the user interest preferences mobile behavior, social network analysis, the second is combined with the physical, social dual space Crowd-sourcing task information propagation, third is the use of optimized algorithm to choose the best collection of workers, and has been conducted on real data sets, the results show that paper method on the premise of guarantee the task completion promoted the rapid spread of task efficiently and high reliability, reasonable resource calls.