This paper presents ranx, a Python evaluation library for Information Retrieval built on top of Numba. ranx provides a user-friendly interface to the most common ranking evaluation metrics, such as MAP, MRR, and NDCG. Moreover, it offers a convenient way of managing the evaluation results, comparing different runs, performing statistical tests between them, and exporting LaTeX tables ready to be used in scientific publications, all in a few lines of code. The efficiency brought by Numba, a just-in-time compiler for Python code, makes the adoption ranx convenient even for industrial applications.

Bassani, E. (2022). ranx: A Blazing-Fast Python Library for Ranking Evaluation and Comparison. In Advances in Information Retrieval. ECIR 2022 (pp.259-264). GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND : Springer Science and Business Media Deutschland GmbH [10.1007/978-3-030-99739-7_30].

ranx: A Blazing-Fast Python Library for Ranking Evaluation and Comparison

Bassani E.
Primo
2022

Abstract

This paper presents ranx, a Python evaluation library for Information Retrieval built on top of Numba. ranx provides a user-friendly interface to the most common ranking evaluation metrics, such as MAP, MRR, and NDCG. Moreover, it offers a convenient way of managing the evaluation results, comparing different runs, performing statistical tests between them, and exporting LaTeX tables ready to be used in scientific publications, all in a few lines of code. The efficiency brought by Numba, a just-in-time compiler for Python code, makes the adoption ranx convenient even for industrial applications.
paper
Comparison; Evaluation; Information Retrieval;
English
44th European Conference on Information Retrieval, ECIR 2022 - 10 April 2022 through 14 April 2022
2022
Advances in Information Retrieval. ECIR 2022
978-3-030-99738-0
2022
13186 LNCS
259
264
none
Bassani, E. (2022). ranx: A Blazing-Fast Python Library for Ranking Evaluation and Comparison. In Advances in Information Retrieval. ECIR 2022 (pp.259-264). GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND : Springer Science and Business Media Deutschland GmbH [10.1007/978-3-030-99739-7_30].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/392847
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