Modeling information retrieval by formal logic: A survey
| Autor: | Karam Abdulahhad, Jean-Pierre Chevallet, Gabriella Pasi, Catherine Berrut |
|---|---|
| Přispěvatelé: | Abdulahhad, K, Berrut, C, Chevallet, J, Pasi, G, Laboratoire d'Informatique de Grenoble (LIG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Università degli Studi di Milano-Bicocca [Milano] (UNIMIB) |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Information retrieval
General Computer Science Basis (linear algebra) Computer science Research areas Process (engineering) Uncertainty Inference 02 engineering and technology Formal logic Logical model [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] Theoretical Computer Science Upgrade Categorization [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR] 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Survey Information retrieval model |
| Zdroj: | ACM Computing Surveys ACM Computing Surveys, Association for Computing Machinery, 2019, 52 (1), ⟨10.1145/3291043⟩ |
| ISSN: | 0360-0300 |
| Popis: | International audience; Several mathematical frameworks have been used to model the information retrieval (IR) process, among them, formal logics. Logic-based IR models upgrade the IR process from document-query comparison to an inference process, in which both documents and queries are expressed as sentences of the selected formal logic. The underlying formal logic also permits one to represent and integrate knowledge in the IR process. One of the main obstacles that has prevented the adoption and large-scale diffusion of logic-based IR systems is their complexity. However, several logic-based IR models have been recently proposed that are applicable to large-scale data collections. In this survey, we present an overview of the most prominent logical IR models that have been proposed in the literature. The considered logical models are categorized under different axes, which include the considered logics and the way in which uncertainty has been modeled, for example, degrees of belief or degrees of truth. Accordingly, the main contribution of the article is to categorize the state-of-the-art logical models on a fine-grained basis, and for the considered models the related implementation aspects are described. Consequently, the proposed survey is finalized to better understand and compare the different logical IR models. Last, but not least, this article aims at reconsidering the potentials of logical approaches to IR by outlining the advances of logic-based approaches in close research areas. |
| Databáze: | OpenAIRE |
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