Abstract Ensuring reproducibility is key to all scientific domains. As Information Retrieval (IR) experiments are often composed of several steps that can be shared between tested models, and rely on various resources, it is difficult to keep track of all the experimental settings and to ensure experiments can be reproduced easily. In this demo paper, we present two managers, Experimaestro and Datamaestro, and their add-ons for IR, designed to help to define and run experimental plans.
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Experimaestro and Datamaestro: Experiment and Dataset Managers (for IR)
Semantic Scholar · Computer Science · 2020
Abstract
Abstract Ensuring reproducibility is key to all scientific domains. As Information Retrieval (IR) experiments are often composed of several steps that can be shared between tested models, and rely on various resources, it is difficult to keep track of all the experimental settings and to ensure experiments can be reproduced easily. In this demo paper, we present two managers, Experimaestro and Datamaestro, and their add-ons for IR, designed to help to define and run experimental plans.