Summary of Messirve: a Large-scale Spanish Information Retrieval Dataset, by Francisco Valentini et al.
MessIRve: A Large-Scale Spanish Information Retrieval Dataset
by Francisco Valentini, Viviana Cotik, Damián Furman, Ivan Bercovich, Edgar Altszyler, Juan Manuel Pérez
First submitted to arxiv on: 9 Sep 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces MessIRve, a large-scale Spanish information retrieval (IR) dataset containing around 730 thousand queries from Google’s autocomplete API and relevant documents sourced from Wikipedia. This dataset is designed to reflect diverse Spanish-speaking regions, unlike existing datasets that are often translated from English or do not consider dialectal variations. The authors provide a comprehensive description of the dataset, comparisons with existing datasets, and baseline evaluations of prominent IR models. The goal is to advance Spanish IR research and improve information access for Spanish speakers. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary MessIRve is a big database that helps computers find important documents in response to what people are searching for online. Right now, there aren’t many ways for Spanish speakers to search for things they want because most of the databases don’t have much Spanish data. This paper creates a huge dataset with over 730 thousand searches and answers from Wikipedia. The searches cover different parts of Spain and Latin America, so it’s not just like translating English searches into Spanish. This database will help computers find better answers to what Spanish speakers are looking for online. |
