The Dagstuhl Perspectives Workshop on Performance Modeling and Prediction

Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Joseph A. Konstan, Pablo Castells, Elizabeth M. Daly, Thierry Declerck, Michael D. Ekstrand, Nava Tintarev, More Authors

Research output: Contribution to journalArticleScientificpeer-review

41 Downloads (Pure)


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
Issue number1
Publication statusPublished - 2018

Bibliographical note

Accepted author manuscript


Dive into the research topics of 'The Dagstuhl Perspectives Workshop on Performance Modeling and Prediction'. Together they form a unique fingerprint.

Cite this