TY - JOUR
T1 - The Dagstuhl Perspectives Workshop on Performance Modeling and Prediction
AU - Ferro, Nicola
AU - Fuhr, Norbert
AU - Grefenstette, Gregory
AU - Konstan, Joseph A.
AU - Castells, Pablo
AU - Daly, Elizabeth M.
AU - Declerck, Thierry
AU - Ekstrand, Michael D.
AU - Tintarev, Nava
AU - More Authors, null
N1 - Accepted author manuscript
PY - 2018
Y1 - 2018
N2 - This paper reports the findings of the Dagstuhl Perspectives Workshop 17442 on performance modeling and prediction in the domains of Information Retrieval, Natural language Processing and Recommender Systems. We present a framework for further research, which identifies five major problem areas: understanding measures, performance analysis, making underlying assumptions explicit, identifying application features determining performance, and the development of prediction models describing the relationship between assumptions, features and resulting performance.
AB - This paper reports the findings of the Dagstuhl Perspectives Workshop 17442 on performance modeling and prediction in the domains of Information Retrieval, Natural language Processing and Recommender Systems. We present a framework for further research, which identifies five major problem areas: understanding measures, performance analysis, making underlying assumptions explicit, identifying application features determining performance, and the development of prediction models describing the relationship between assumptions, features and resulting performance.
U2 - 10.1145/3274784.3274789
DO - 10.1145/3274784.3274789
M3 - Article
SN - 0163-5840
VL - 52
SP - 91
EP - 101
JO - ACM SIGIR Forum
JF - ACM SIGIR Forum
IS - 1
ER -