Author:
Ferro Nicola,Fuhr Norbert,Grefenstette Gregory,Konstan Joseph A.,Castells Pablo,Daly Elizabeth M.,Declerck Thierry,Ekstrand Michael D.,Geyer Werner,Gonzalo Julio,Kuflik Tsvi,Lindn Krister,Magnini Bernardo,Nie Jian-Yun,Perego Raffaele,Shapira Bracha,Soboroff Ian,Tintarev Nava,Verspoor Karin,Willemsen Martijn C.,Zobel Justin
Abstract
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.
Publisher
Association for Computing Machinery (ACM)
Subject
Hardware and Architecture,Management Information Systems
Cited by
12 articles.
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