TY - GEN
T1 - Crowd-sourcing user participant recruitment method based on geo-social network
AU - Cheng, Yong
AU - Wang, Tongyu
AU - Wang, Liang
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/6
Y1 - 2020/6
N2 - 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.
AB - 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.
KW - Crowd-Sourcing participant recruitment
KW - Information propagation model
KW - mobile behavior characteristics
KW - social network
UR - http://www.scopus.com/inward/record.url?scp=85086248160&partnerID=8YFLogxK
U2 - 10.1109/ITNEC48623.2020.9085174
DO - 10.1109/ITNEC48623.2020.9085174
M3 - 会议稿件
AN - SCOPUS:85086248160
T3 - Proceedings of 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2020
SP - 2193
EP - 2197
BT - Proceedings of 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2020
A2 - Xu, Bing
A2 - Mou, Kefen
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2020
Y2 - 12 June 2020 through 14 June 2020
ER -
