Print Email Facebook Twitter The Dagstuhl Perspectives Workshop on Performance Modeling and Prediction Title The Dagstuhl Perspectives Workshop on Performance Modeling and Prediction Author Ferro, Nicola (University of Padua) Fuhr, Norbert (External organisation) Grefenstette, Gregory (External organisation) Konstan, Joseph A. (Association for Computing Machinery (ACM)) Castells, Pablo (External organisation) Daly, Elizabeth M. (External organisation) Declerck, Thierry (External organisation) Ekstrand, Michael D. (Boise State University) Tintarev, N. (TU Delft Web Information Systems) Date 2018 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. To reference this document use: http://resolver.tudelft.nl/uuid:50964ba5-0729-4a7d-bd06-346eb9a444cc DOI https://doi.org/10.1145/3274784.3274789 ISSN 0163-5840 Source ACM SIGIR Forum, 52 (1), 91-101 Bibliographical note Accepted author manuscript Part of collection Institutional Repository Document type journal article Rights © 2018 Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Joseph A. Konstan, Pablo Castells, Elizabeth M. Daly, Thierry Declerck, Michael D. Ekstrand, N. Tintarev, More Authors Files PDF 45183054_performance_pred ... ion_ir.pdf 317.51 KB Close viewer /islandora/object/uuid:50964ba5-0729-4a7d-bd06-346eb9a444cc/datastream/OBJ/view