129 citations · 332 across the 11 of their papers we have counts for
11 papers
Link Prediction in Bipartite Networks
Şükrü Demir İnan Özer, Günce Keziban Orman, Vincent Labatut
Bipartite networks serve as highly suitable models to represent systems involving interactions between two distinct types of entities, such as online dating platforms, job search s…
Finding Proper Time Intervals for Dynamic Network Extraction
Günce Keziban Orman, Nadir Türe, Selim Balcisoy +1
Extracting a proper dynamic network for modelling a time-dependent complex system is an important issue. Building a correct model is related to finding out critical time points whe…
Exploring the Evolution of Node Neighborhoods in Dynamic Networks
Günce Keziban Orman, Vincent Labatut, Ahmet Teoman Naskali
Dynamic Networks are a popular way of modeling and studying the behavior of evolving systems. However, their analysis constitutes a relatively recent subfield of Network Science, a…
Community Structure Characterization
Vincent Labatut, Günce Keziban Orman
This entry discusses the problem of describing some communities identified in a complex network of interest, in a way allowing to interpret them. We suppose the community structure…
Interpreting communities based on the evolution of a dynamic attributed network
Günce Orman, Vincent Labatut, Marc Plantevit +1
Many methods have been proposed to detect communities, not only in plain, but also in attributed, directed or even dynamic complex networks. From the modeling point of view, to be…
Une méthode pour caractériser les communautés des réseaux dynamiques à attributs
Günce Keziban Orman, Vincent Labatut, Marc Plantevit +1
Many complex systems are modeled through complex networks whose analysis reveals typical topological properties. Amongst those, the community structure is one of the most studied.…
Towards realistic artificial benchmark for community detection algorithms evaluation
Günce Keziban Orman, Vincent Labatut, Hocine Cherifi
Assessing the partitioning performance of community detection algorithms is one of the most important issues in complex network analysis. Artificially generated networks are often…
Qualitative Comparison of Community Detection Algorithms
Günce Orman, Vincent Labatut, Hocine Cherifi
Community detection is a very active field in complex networks analysis, consisting in identifying groups of nodes more densely interconnected relatively to the rest of the network…
An Empirical Study of the Relation Between Community Structure and Transitivity
Günce Keziban Orman, Vincent Labatut, Hocine Cherifi
One of the most prominent properties in real-world networks is the presence of a community structure, i.e. dense and loosely interconnected groups of nodes called communities. In a…
Comparative Evaluation of Community Detection Algorithms: A Topological Approach
Günce Orman, Vincent Labatut, Hocine Cherifi
Community detection is one of the most active fields in complex networks analysis, due to its potential value in practical applications. Many works inspired by different paradigms…
On Accuracy of Community Structure Discovery Algorithms
Günce Keziban Orman, Vincent Labatut, Hocine Cherifi
Community structure discovery in complex networks is a quite challenging problem spanning many applications in various disciplines such as biology, social network and physics. Emer…