TY - GEN
T1 - Complicated-skills-based task assignment in spatial crowdsourcing
AU - Liu, Jiaxu
AU - Zhu, Haogang
AU - Chen, Xiao
N1 - Publisher Copyright:
© Springer International Publishing AG 2016.
PY - 2016
Y1 - 2016
N2 - Spatial crowdsourcing is an activity consisting in outsourcing spatial tasks to a community of online, yet on-ground and mobile, workers. Presently an increasing number of spatial crowdsourcing applications emerges due to the related technologies tends to maturity. Distinct from traditional crowdsourcing dualistic entities, task and worker, a special kind of applications imports the third one of skill. Consequently, a novel assignment problem called multiple skills assignment problem (MSAP) is generated which extends the entity relationship from 2 to 3 dimensions. Inspired by group strategy we first propose a lightweight algorithm GMA that could achieve approximate optimal solution quickly. However, GMA exists a defect of ignoring that workers with multiple skills can decrease total travel distance significantly. Thus we propose a revised algorithm RGMA to cut down distance cost. With synthetic datasets, we empirically and comparatively evaluate the performance of the baseline and two proposed algorithms.
AB - Spatial crowdsourcing is an activity consisting in outsourcing spatial tasks to a community of online, yet on-ground and mobile, workers. Presently an increasing number of spatial crowdsourcing applications emerges due to the related technologies tends to maturity. Distinct from traditional crowdsourcing dualistic entities, task and worker, a special kind of applications imports the third one of skill. Consequently, a novel assignment problem called multiple skills assignment problem (MSAP) is generated which extends the entity relationship from 2 to 3 dimensions. Inspired by group strategy we first propose a lightweight algorithm GMA that could achieve approximate optimal solution quickly. However, GMA exists a defect of ignoring that workers with multiple skills can decrease total travel distance significantly. Thus we propose a revised algorithm RGMA to cut down distance cost. With synthetic datasets, we empirically and comparatively evaluate the performance of the baseline and two proposed algorithms.
UR - https://www.scopus.com/pages/publications/84995972503
U2 - 10.1007/978-3-319-47121-1_18
DO - 10.1007/978-3-319-47121-1_18
M3 - 会议稿件
AN - SCOPUS:84995972503
SN - 9783319471204
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 211
EP - 223
BT - Web-Age Information Management - WAIM 2016 International Workshops MWDA, SDMMW, and SemiBDMA, Revised Selected Papers
A2 - Tong, Yongxin
A2 - Song, Shaoxu
PB - Springer Verlag
T2 - 17th International Conference on Web-Age Information Management, WAIM 2016
Y2 - 3 June 2016 through 5 June 2016
ER -