TY - GEN
T1 - Mining reliable information from passively and actively crowdsourced data
AU - Gao, Jing
AU - Li, Qi
AU - Zhao, Bo
AU - Fan, Wei
AU - Han, Jiawei
N1 - Publisher Copyright:
© 2016 Copyright held by the owner/author(s).
PY - 2016/8/13
Y1 - 2016/8/13
N2 - Recent years have witnessed an astonishing growth of crowd-contributed data, which has become a powerful information source that covers almost every aspect of our lives. This big treasure trove of information has fundamentally changed the ways in which we learn about our world. Crowdsourcing has attracted considerable attentions with various approaches developed to utilize these enormous crowdsourced data from different perspectives. From the data collection perspective, crowdsourced data can be divided into two types: "passively" crowdsourced data and "actively" crowdsourced data; from task perspective, crowdsourcing research includes information aggregation, budget allocation, worker incentive mechanism, etc. To answer the need of a systematic introduction of the field and comparison of the techniques, we will present an organized picture on crowdsourcing methods in this tuto- rial. The covered topics will be interested for both advanced researchers and beginners in this field.
AB - Recent years have witnessed an astonishing growth of crowd-contributed data, which has become a powerful information source that covers almost every aspect of our lives. This big treasure trove of information has fundamentally changed the ways in which we learn about our world. Crowdsourcing has attracted considerable attentions with various approaches developed to utilize these enormous crowdsourced data from different perspectives. From the data collection perspective, crowdsourced data can be divided into two types: "passively" crowdsourced data and "actively" crowdsourced data; from task perspective, crowdsourcing research includes information aggregation, budget allocation, worker incentive mechanism, etc. To answer the need of a systematic introduction of the field and comparison of the techniques, we will present an organized picture on crowdsourcing methods in this tuto- rial. The covered topics will be interested for both advanced researchers and beginners in this field.
UR - https://www.scopus.com/pages/publications/84985018478
UR - https://www.scopus.com/pages/publications/84985018478#tab=citedBy
U2 - 10.1145/2939672.2945389
DO - 10.1145/2939672.2945389
M3 - Conference contribution
AN - SCOPUS:84985018478
T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
SP - 2121
EP - 2122
BT - KDD 2016 - Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
PB - Association for Computing Machinery
T2 - 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2016
Y2 - 13 August 2016 through 17 August 2016
ER -