Documents

DOI

  • Nicola Ferro
  • Norbert Fuhr
  • Gregory Grefenstette
  • Joseph A. Konstan
  • Pablo Castells
  • Elizabeth M. Daly
  • Thierry Declerck
  • Michael D. Ekstrand
  • Nava Tintarev
  • More Authors
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.
Original languageEnglish
Pages (from-to)91-101
Number of pages11
JournalACM SIGIR Forum
Volume52
Issue number1
DOIs
Publication statusPublished - 2018

ID: 45183054