Arbeitspapier
Recursive Clustering Methods for Network Analysis
We study axiomatically recursive clustering methods for networks. Such methods can be used to identify community structures of a network. One of the methods is based on identifying a node subset that maximizes the average degree within this subset. Once such a subset is found, the method is applied on the subnetwork whose node set is the complement of the first cluster, and so on recursively. The method produces an ordered partition of the node set of the original network. We give a list of axioms that this method satisfies, and show that any recursive clustering method satisfying the same set of axioms must produce the same or a coarser partition than our method.
- Language
-
Englisch
- Bibliographic citation
-
Series: Discussion paper ; No. 118
- Classification
-
Wirtschaft
Cooperative Games
Network Formation and Analysis: Theory
- Subject
-
networks
clustering
community structure
- Event
-
Geistige Schöpfung
- (who)
-
Kitti, Mitri
Pihlava, Matti
Salonen, Hannu
- Event
-
Veröffentlichung
- (who)
-
Aboa Centre for Economics (ACE)
- (where)
-
Turku
- (when)
-
2018
- Handle
- Last update
-
10.03.2025, 11:43 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Kitti, Mitri
- Pihlava, Matti
- Salonen, Hannu
- Aboa Centre for Economics (ACE)
Time of origin
- 2018
Other Objects (12)
Parameterized algorithmics for network analysis : clustering & querying
Parameterized Algorithmics for Network Analysis: Clustering & Querying
Assessing clustering methods for exploratory spatial data analysis
Recursive Partitioning and Tree-based Methods
Clustering with Spectral Methods
Analysis and evaluation of data preprocessing methods for clustering analyses
Network ensemble clustering using latent roles
Geometrical methods for power network analysis
Exploratory subgroup analysis by recursive segmentation
Quantile regression methods for recursive structural equation models
Isotone Recursive Methods: the Case of Homogeneous Agents
Algorithms for fuzzy clustering : methods in c-means clustering with applications
Parameterized algorithmics for network analysis : clustering & querying
Parameterized Algorithmics for Network Analysis: Clustering & Querying
Assessing clustering methods for exploratory spatial data analysis
Recursive Partitioning and Tree-based Methods
Clustering with Spectral Methods
Analysis and evaluation of data preprocessing methods for clustering analyses
Network ensemble clustering using latent roles
Geometrical methods for power network analysis
Exploratory subgroup analysis by recursive segmentation
Quantile regression methods for recursive structural equation models
Isotone Recursive Methods: the Case of Homogeneous Agents
Algorithms for fuzzy clustering : methods in c-means clustering with applications
Parameterized algorithmics for network analysis : clustering & querying
Parameterized Algorithmics for Network Analysis: Clustering & Querying
Assessing clustering methods for exploratory spatial data analysis
Recursive Partitioning and Tree-based Methods
Clustering with Spectral Methods
Analysis and evaluation of data preprocessing methods for clustering analyses
Network ensemble clustering using latent roles
Geometrical methods for power network analysis
Exploratory subgroup analysis by recursive segmentation
Quantile regression methods for recursive structural equation models
Isotone Recursive Methods: the Case of Homogeneous Agents