Aisberg: dal 2009 è l'archivio ad accesso aperto dell'Università di Bergamo; dal 2011 è anche l'anagrafe della ricerca di Ateneo.
L'archivio è un'implementazione di IRIS, il sistema informativo per la ricerca sviluppato da Cineca.
EnglishThe use of networks for modelling and analysing relations among data is currently growing. Recently, the use of a single networks for capturing all the aspects of some complex scenarios has shown some limitations. Consequently, it has been proposed to use Dual Networks (DN), a pair of related networks, to analyse complex systems. The two graphs in a DN have the same set of vertices and different edge sets. Common subgraphs among these networks may convey some insights about the modelled scenarios. For instance, the detection of the Top-k Densest Connected subgraphs, i.e. a set k subgraphs having the largest density in the conceptual network which are also connected in the physical network, may reveal set of highly related nodes. After proposing a formalisation of the approach, we propose a heuristic to find a solution, since the problem is computationally hard. A set of experiments on synthetic and real networks is also presented to support our approach.
(2021). A novel algorithm for finding top-k weighted overlapping densest connected subgraphs in dual networks [journal article - articolo]. In APPLIED NETWORK SCIENCE. Retrieved from http://hdl.handle.net/10446/200860
| Citazione: | (2021). A novel algorithm for finding top-k weighted overlapping densest connected subgraphs in dual networks [journal article - articolo]. In APPLIED NETWORK SCIENCE. Retrieved from http://hdl.handle.net/10446/200860 | |
| Titolo: | A novel algorithm for finding top-k weighted overlapping densest connected subgraphs in dual networks | |
| Tipologia specifica: | articolo | |
| Tutti gli autori: | Dondi, Riccardo; Hosseinzadeh, Mohammad Mehdi; Guzzi, Pietro H. | |
| Data di pubblicazione: | 2021 | |
| Abstract (eng): | The use of networks for modelling and analysing relations among data is currently growing. Recently, the use of a single networks for capturing all the aspects of some complex scenarios has shown some limitations. Consequently, it has been proposed to use Dual Networks (DN), a pair of related networks, to analyse complex systems. The two graphs in a DN have the same set of vertices and different edge sets. Common subgraphs among these networks may convey some insights about the modelled scenarios. For instance, the detection of the Top-k Densest Connected subgraphs, i.e. a set k subgraphs having the largest density in the conceptual network which are also connected in the physical network, may reveal set of highly related nodes. After proposing a formalisation of the approach, we propose a heuristic to find a solution, since the problem is computationally hard. A set of experiments on synthetic and real networks is also presented to support our approach. | |
| Rivista: | ||
| Nelle collezioni: | 1.1.01 Articoli/Saggi in rivista - Journal Articles/Essays |
File allegato/i alla scheda:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| Applied_Network_Science2021.pdf | publisher's version - versione editoriale |  | Open AccessVisualizza/Apri |
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