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.
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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, |
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dig-cirad-fr-6058962024-06-11T09:38:12Z http://agritrop.cirad.fr/605896/ http://agritrop.cirad.fr/605896/ Introduction to the Special Section on reloading feature-rich information networks. Tagarelli Andrea (ed.), Gaito Sabrina (ed.), Interdonato Roberto (ed.), Murata Tsuyoshi (ed.), Sala Alessandra (ed.), Thai My T. (ed.). 2021. IEEE Transactions on Network Science and Engineering, 8 (2) : 1256-1258.https://doi.org/10.1109/TNSE.2021.3073824 <https://doi.org/10.1109/TNSE.2021.3073824> Introduction to the Special Section on reloading feature-rich information networks Tagarelli, Andrea (ed.) Gaito, Sabrina (ed.) Interdonato, Roberto (ed.) Murata, Tsuyoshi (ed.) Sala, Alessandra (ed.) Thai, My T. (ed.) eng 2021 IEEE Transactions on Network Science and Engineering 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 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. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/605896/1/ID605896.pdf text Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1109/TNSE.2021.3073824 10.1109/TNSE.2021.3073824 info:eu-repo/semantics/altIdentifier/doi/10.1109/TNSE.2021.3073824 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1109/TNSE.2021.3073824 |
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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 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 |
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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 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 Tagarelli, Andrea (ed.) Gaito, Sabrina (ed.) Interdonato, Roberto (ed.) Murata, Tsuyoshi (ed.) Sala, Alessandra (ed.) Thai, My T. (ed.) Introduction to the Special Section on reloading feature-rich information networks |
description |
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. |
format |
article |
topic_facet |
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 |
author |
Tagarelli, Andrea (ed.) Gaito, Sabrina (ed.) Interdonato, Roberto (ed.) Murata, Tsuyoshi (ed.) Sala, Alessandra (ed.) Thai, My T. (ed.) |
author_facet |
Tagarelli, Andrea (ed.) Gaito, Sabrina (ed.) Interdonato, Roberto (ed.) Murata, Tsuyoshi (ed.) Sala, Alessandra (ed.) Thai, My T. (ed.) |
author_sort |
Tagarelli, Andrea (ed.) |
title |
Introduction to the Special Section on reloading feature-rich information networks |
title_short |
Introduction to the Special Section on reloading feature-rich information networks |
title_full |
Introduction to the Special Section on reloading feature-rich information networks |
title_fullStr |
Introduction to the Special Section on reloading feature-rich information networks |
title_full_unstemmed |
Introduction to the Special Section on reloading feature-rich information networks |
title_sort |
introduction to the special section on reloading feature-rich information networks |
url |
http://agritrop.cirad.fr/605896/ http://agritrop.cirad.fr/605896/1/ID605896.pdf |
work_keys_str_mv |
AT tagarelliandreaed introductiontothespecialsectiononreloadingfeaturerichinformationnetworks AT gaitosabrinaed introductiontothespecialsectiononreloadingfeaturerichinformationnetworks AT interdonatorobertoed introductiontothespecialsectiononreloadingfeaturerichinformationnetworks AT muratatsuyoshied introductiontothespecialsectiononreloadingfeaturerichinformationnetworks AT salaalessandraed introductiontothespecialsectiononreloadingfeaturerichinformationnetworks AT thaimyted introductiontothespecialsectiononreloadingfeaturerichinformationnetworks |
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1802821398383558656 |