Recent entity-based retrieval models utilizing knowledge bases have shown significant
improvement in ad-hoc retrieval. However, a lack of coherence between candidate entities …

Artificial graphs are commonly used for the evaluation of community mining and clustering
algorithms. Each artificial graph is assigned a pre-specified clustering, which is compared to …

Sharing nearest neighbor (SNN) is a novel metric measure of similarity, and it can conquer
two hardships: the low similarities between samples and the different densities of classes. At …

Detecting communities in a network can be helpful to comprehend its structure and
understand its function. The detecting-communities approach, in essence, is a model of …

The vertex-clustering algorithm based on intra connection ratio (MV-ICR algorithm) is a
graph-clustering algorithm proposed by Moussiades and Vakali [Clustering dense graph: A …

This paper proposes a new clustering coefficient based on the number of connecting
vertices within a cluster (called inter vertex adjacent ratio, IVAR) and proposes a new …

This paper introduce a gradient weighting based fuzzy clustering algorithm for graph data, in
which the clustering process can be regarded as an optimization for objective function …

Linear hybrid automaton is a specification language for hybrid systems. For verification of
hybrid systems, it is important to check fairness assumptions. For example, an embedded …

Interactions among neurons can take place in a wide variety of forms. It is the goal of this
thesis to investigate the properties and implications of a number of these interactions that we …