TY - GEN
T1 - InCognitoMatch
T2 - 2020 ACM SIGMOD International Conference on Management of Data, SIGMOD 2020
AU - Shraga, Roee
AU - Scharf, Coral
AU - Ackerman, Rakefet
AU - Gal, Avigdor
N1 - Publisher Copyright:
© 2020 Association for Computing Machinery.
PY - 2020/6/14
Y1 - 2020/6/14
N2 - We present InCognitoMatch, the first cognitive-aware crowdsourcing application for matching tasks. InCognitoMatch provides a handy tool to validate, annotate, and correct correspondences using the crowd whilst accounting for human matching biases. In addition, InCognitoMatch enables system administrators to control context information visible for workers and analyze their performance accordingly. For crowd workers, InCognitoMatch is an easy-to-use application that may be accessed from multiple crowdsourcing platforms. In addition, workers completing a task are offered suggestions for followup sessions according to their performance in the current session. For this demo, the audience will be able to experience InCognitoMatch thorough three use-cases, interacting with system as workers and as administrators.
AB - We present InCognitoMatch, the first cognitive-aware crowdsourcing application for matching tasks. InCognitoMatch provides a handy tool to validate, annotate, and correct correspondences using the crowd whilst accounting for human matching biases. In addition, InCognitoMatch enables system administrators to control context information visible for workers and analyze their performance accordingly. For crowd workers, InCognitoMatch is an easy-to-use application that may be accessed from multiple crowdsourcing platforms. In addition, workers completing a task are offered suggestions for followup sessions according to their performance in the current session. For this demo, the audience will be able to experience InCognitoMatch thorough three use-cases, interacting with system as workers and as administrators.
KW - cognitive-aware
KW - crowdsourcing
KW - data integration
KW - matching
UR - http://www.scopus.com/inward/record.url?scp=85086248703&partnerID=8YFLogxK
U2 - 10.1145/3318464.3384697
DO - 10.1145/3318464.3384697
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AN - SCOPUS:85086248703
T3 - Proceedings of the ACM SIGMOD International Conference on Management of Data
SP - 2753
EP - 2756
BT - SIGMOD 2020 - Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data
Y2 - 14 June 2020 through 19 June 2020
ER -