Abstract
We describe the state-of-the-art in performance modeling and prediction for Information Retrieval (IR), Natural Language Processing (NLP) and Recommender Systems (RecSys) along with its shortcomings and strengths. We present a framework for further research, identifying 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 language | English |
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Pages (from-to) | 96-139 |
Number of pages | 44 |
Journal | Dagstuhl Manifestos |
Volume | 7 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2019 |
Event | Perspectives Workshop - Schloss Dagatuhl, Wadern, Germany Duration: 30 Oct 2019 → 3 Nov 2019 |