TY - CHAP
T1 - Worker skill estimation in team-based tasks
AU - Rahman, Habibur
AU - Thirumuruganathan, Saravanan
AU - Roy, Senjuti Basu
AU - Amer-Yahia, Sihem
AU - Das, Gautam
N1 - Publisher Copyright:
© 2015 VLDB Endowment 2150-8097/15/07
PY - 2015
Y1 - 2015
N2 - Many emerging applications such as collaborative editing, multi-player games, or fan-subbing require to form a team of experts to accomplish a task together. Existing research has investigated how to assign workers to such team-based tasks to ensure the best outcome assuming the skills of individual workers to be known. In this work, we investigate how to estimate individual worker's skill based on the outcome of the team-based tasks they have undertaken. We consider two popular skill aggregation functions and estimate the skill of the workers, where skill is either a deterministic value or a probability distribution. We propose effcient solutions for worker skill estimation using continuous and discrete optimization techniques. We present comprehensive experiments and validate the scalability and effectiveness of our proposed solutions using multiple real-world datasets.
AB - Many emerging applications such as collaborative editing, multi-player games, or fan-subbing require to form a team of experts to accomplish a task together. Existing research has investigated how to assign workers to such team-based tasks to ensure the best outcome assuming the skills of individual workers to be known. In this work, we investigate how to estimate individual worker's skill based on the outcome of the team-based tasks they have undertaken. We consider two popular skill aggregation functions and estimate the skill of the workers, where skill is either a deterministic value or a probability distribution. We propose effcient solutions for worker skill estimation using continuous and discrete optimization techniques. We present comprehensive experiments and validate the scalability and effectiveness of our proposed solutions using multiple real-world datasets.
UR - http://www.scopus.com/inward/record.url?scp=84953863006&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84953863006&partnerID=8YFLogxK
U2 - 10.14778/2809974.2809977
DO - 10.14778/2809974.2809977
M3 - Chapter
AN - SCOPUS:84953863006
T3 - Proceedings of the VLDB Endowment
SP - 1142
EP - 1153
BT - Proceedings of the VLDB Endowment
PB - Association for Computing Machinery
T2 - 3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006
Y2 - 11 September 2006 through 11 September 2006
ER -