In the dynamic field of information retrieval, the adoption of graph-based approaches has become a notable research trend. Fueled by the growing research on Knowledge Graphs and Graph Neural Networks, these approaches rooted in graph theory have shown significant promise in enhancing the effectiveness and relevance of information retrieval results. With this motivation in mind, this workshop serves as a platform, bringing together researchers and practitioners from diverse backgrounds, to delve into and discuss the integration of modern graph-based methodologies into information retrieval methods. The workshop website is available at https://irongraphs.github.io/ecir2024/.

First International Workshop on Graph-Based Approaches in Information Retrieval (IRonGraphs 2024)

Boratto L.;Marras M.;Medda G.;
2024-01-01

Abstract

In the dynamic field of information retrieval, the adoption of graph-based approaches has become a notable research trend. Fueled by the growing research on Knowledge Graphs and Graph Neural Networks, these approaches rooted in graph theory have shown significant promise in enhancing the effectiveness and relevance of information retrieval results. With this motivation in mind, this workshop serves as a platform, bringing together researchers and practitioners from diverse backgrounds, to delve into and discuss the integration of modern graph-based methodologies into information retrieval methods. The workshop website is available at https://irongraphs.github.io/ecir2024/.
2024
9783031560682
9783031560699
Algorithms
Graph Neural Networks
Graphs
Information Retrieval
Knowledge Graphs
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Search
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/432654
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