Abstract

{#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 Semantic Scholar