Information Retrieval: Recent Advances and Beyond
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2023
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866917590397353984 |
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| author | Hambarde, Kailash A. Proenca, Hugo |
| author_facet | Hambarde, Kailash A. Proenca, Hugo |
| contents | In this paper, we provide a detailed overview of the models used for information retrieval in the first and second stages of the typical processing chain. We discuss the current state-of-the-art models, including methods based on terms, semantic retrieval, and neural. Additionally, we delve into the key topics related to the learning process of these models. This way, this survey offers a comprehensive understanding of the field and is of interest for for researchers and practitioners entering/working in the information retrieval domain. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2301_08801 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Information Retrieval: Recent Advances and Beyond Hambarde, Kailash A. Proenca, Hugo Information Retrieval In this paper, we provide a detailed overview of the models used for information retrieval in the first and second stages of the typical processing chain. We discuss the current state-of-the-art models, including methods based on terms, semantic retrieval, and neural. Additionally, we delve into the key topics related to the learning process of these models. This way, this survey offers a comprehensive understanding of the field and is of interest for for researchers and practitioners entering/working in the information retrieval domain. |
| title | Information Retrieval: Recent Advances and Beyond |
| topic | Information Retrieval |
| url | https://arxiv.org/abs/2301.08801 |