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.

Links

• SIGIR Forum article

Listed Under

• Reliable Recommender Systems Research

Recorded Elsewhere

• Version of Record
• Entry in Microsoft Academic
• Entry in Semantic Scholar