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Conference Papers Year : 2022

CHERCHE: A New Tool to Rapidly Implement Pipelines in Information Retrieval

Abstract

In this demo paper, we present a new open-source python module for building information retrieval pipelines with transformers namely CHERCHE. Our aim is to propose an easy to plug tool capable to execute, simple but strong, state-of-the-art information retrieval models. To do so, we have integrated classical models based on lexical matching but also recent models based on semantic matching. Indeed, a large number of models available on public hubs can be now tested on information retrieval tasks with only a few lines. CHERCHE is oriented to newcomers into the neural information retrieval field that want to use transformer-based models in small collections without struggling with heavy tools. The code and documentation of CHERCHE is public available at https://github.com/raphaelsty/cherche
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Dates and versions

hal-03885055 , version 1 (06-12-2022)

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Raphaël Sourty, Jose G. Moreno, Lynda Tamine, François-Paul Servant. CHERCHE: A New Tool to Rapidly Implement Pipelines in Information Retrieval. 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022), ACM SIGIR: Special Interest Group in Information Retrieval, Jul 2022, Madrid, Spain. pp.3283-3288, ⟨10.1145/3477495.3531695⟩. ⟨hal-03885055⟩
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