This manuscript discusses our ongoing work on ranx, a Python evaluation library for Information Retrieval. First, we introduce our work, summarize the already available functionalities, show the user-friendly nature of our tool through code snippets, and briefly discuss the technologies we relied on for the implementation and their advantages. Then, we present the upcoming features, such as several Metasearch algorithms, and introduce the long-term goals of our project.

Bassani, E. (2022). Towards an Information Retrieval Evaluation Library. In CEUR Workshop Proceedings. CEUR-WS.

Towards an Information Retrieval Evaluation Library

Bassani E.
Primo
2022

Abstract

This manuscript discusses our ongoing work on ranx, a Python evaluation library for Information Retrieval. First, we introduce our work, summarize the already available functionalities, show the user-friendly nature of our tool through code snippets, and briefly discuss the technologies we relied on for the implementation and their advantages. Then, we present the upcoming features, such as several Metasearch algorithms, and introduce the long-term goals of our project.
No
abstract
Comparison; Evaluation; Fusion; Information Retrieval; Metasearch;
English
12th Italian Information Retrieval Workshop, IIR 2022 - 29 June 2022 through 30 June 2022
Bassani, E. (2022). Towards an Information Retrieval Evaluation Library. In CEUR Workshop Proceedings. CEUR-WS.
Bassani, E
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/392848
Citazioni
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
Social impact