Introduction to the Special Section on reloading feature-rich information networks
The articles in this special section focus on the reloading of feature-rich information networks. The growing availability of multi-facetedrelational data gives rise to unprecedented opportunities for unveiling complex real-world behaviors and phenomena. This also supports the proliferation of complex network models where the expressive power of the graph-based relational structure is enhanced through exposing several types of features that are peculiar of the domain-specific environment (e.g., social media platforms, biological environment, geographical location). Examples of feature-rich networks include heterogeneous information networks, multilayer networks, temporal networks, location-aware networks, and probabilistic networks. The aim of the special section is to address challenging issues and emerging trends in feature-rich information networks that can be mined in various domains.
| Main Authors: | , , , , , |
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| Format: | article biblioteca |
| Language: | eng |
| Subjects: | C30 - Documentation et information, U10 - Informatique, mathématiques et statistiques, information, gestion de l'information, analyse de données, traitement des données, http://aims.fao.org/aos/agrovoc/c_330966, http://aims.fao.org/aos/agrovoc/c_49838, http://aims.fao.org/aos/agrovoc/c_15962, http://aims.fao.org/aos/agrovoc/c_10289, |
| Online Access: | http://agritrop.cirad.fr/605896/ http://agritrop.cirad.fr/605896/1/ID605896.pdf |
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| Summary: | The articles in this special section focus on the reloading of feature-rich information networks. The growing availability of multi-facetedrelational data gives rise to unprecedented opportunities for unveiling complex real-world behaviors and phenomena. This also supports the proliferation of complex network models where the expressive power of the graph-based relational structure is enhanced through exposing several types of features that are peculiar of the domain-specific environment (e.g., social media platforms, biological environment, geographical location). Examples of feature-rich networks include heterogeneous information networks, multilayer networks, temporal networks, location-aware networks, and probabilistic networks. The aim of the special section is to address challenging issues and emerging trends in feature-rich information networks that can be mined in various domains. |
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