TY - GEN
T1 - Users, adaptivity, and bad abandonment
AU - Moffat, Alistair
AU - Wicaksono, Alfan Farizki
N1 - Publisher Copyright:
© 2018 ACM.
PY - 2018/6/27
Y1 - 2018/6/27
N2 - We consider two recent proposals for effectiveness metrics that have been argued to be adaptive, those of Moffat et al. (ACM TOIS, 2017) and Jiang and Allan (CIKM, 2017), and consider the user interaction models that they give rise to. By categorizing non-relevant documents into those that are plausibly non-relevant and those that are egregiously non-relevant, we capture all of the attributes incorporated into the two proposals, and hence develop an effectiveness metric that better reflects user behavior when viewing the SERP, including bad abandonment.
AB - We consider two recent proposals for effectiveness metrics that have been argued to be adaptive, those of Moffat et al. (ACM TOIS, 2017) and Jiang and Allan (CIKM, 2017), and consider the user interaction models that they give rise to. By categorizing non-relevant documents into those that are plausibly non-relevant and those that are egregiously non-relevant, we capture all of the attributes incorporated into the two proposals, and hence develop an effectiveness metric that better reflects user behavior when viewing the SERP, including bad abandonment.
KW - Adaptive
KW - Evaluation
KW - Precision
KW - User model
UR - http://www.scopus.com/inward/record.url?scp=85051522197&partnerID=8YFLogxK
U2 - 10.1145/3209978.3210075
DO - 10.1145/3209978.3210075
M3 - Conference contribution
AN - SCOPUS:85051522197
T3 - 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018
SP - 897
EP - 900
BT - 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018
PB - Association for Computing Machinery, Inc
T2 - 41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018
Y2 - 8 July 2018 through 12 July 2018
ER -