Properties of Bipolar Fuzzy Hypergraphs

In this article, we apply the concept of bipolar fuzzy sets to hypergraphs and investigate some properties of bipolar fuzzy hypergraphs. We introduce the notion of $A-$ tempered bipolar fuzzy hypergraphs and present some of their properties. We also present application examples of bipolar fuzzy hypergraphs

Term-Specific Eigenvector-Centrality in Multi-Relation Networks

Fuzzy matching and ranking are two information retrieval techniques widely used in web search. Their application to structured data, however, remains an open problem. This article investigates how eigenvector-centrality can be used for approximate matching in multi-relation graphs, that is, graphs where connections of many different types may exist. Based on an extension of the PageRank matrix, eigenvectors representing the distribution of a term after propagating term weights between related data items are computed. The result is an index which takes the document structure into account and can be used with standard document retrieval techniques. As the scheme takes the shape of an index transformation, all necessary calculations are performed during index tim

Towards Quantum Dielectric Branes: Curvature Corrections in Abelian Beta Function and Nonabelian Born-Infeld Action

We initiate a programme to compute curvature corrections to the nonabelian BI action. This is based on the calculation of derivative corrections to the abelian BI action, describing a maximal brane, to all orders in F. An exact calculation in F allows us to apply the SW map, reducing the maximal abelian point of view to a minimal nonabelian point of view (replacing 1/F with [X,X] at large F), resulting in matrix model equations of motion. We first study derivative corrections to the abelian BI action and compute the 2-loop beta function for an open string in a WZW (parallelizable) background. This beta function is the first step in the process of computing string equations of motion, which can be later obtained by computing the Weyl anomaly coefficients or the partition function. The beta function is exact in F and computed to orders O(H,H^2,H^3) (H=dB and curvature is R ~ H^2) and O(DF,D^2F,D^3F). In order to carry out this calculation we develop a new regularization method for 2-loop graphs. We then relate perturbative results for abelian and nonabelian BI actions, by showing how abelian derivative corrections yield nonabelian commutator corrections, at large F. We begin the construction of a matrix model describing \a' corrections to Myers' dielectric effect. This construction is carried out by setting up a perturbative classification of the relevant nonabelian tensor structures, which can be considerably narrowed down by the constraint of translation invariance in the action and the possibility for generic field redefinitions. The final matrix action is not uniquely determined and depends upon two free parameters. These parameters could be computed via further calculations in the abelian theory.Comment: JHEP3.cls, 64 pages, 3 figures; v2: added references; v3: more references, final version for NP

Gauge Theories on Deformed Spaces

The aim of this review is to present an overview over available models and approaches to non-commutative gauge theory. Our main focus thereby is on gauge models formulated on flat Groenewold-Moyal spaces and renormalizability, but we will also review other deformations and try to point out common features. This review will by no means be complete and cover all approaches, it rather reflects a highly biased selection.Comment: v2 references added; v3 published versio

A similarity-based community detection method with multiple prototype representation

Communities are of great importance for understanding graph structures in social networks. Some existing community detection algorithms use a single prototype to represent each group. In real applications, this may not adequately model the different types of communities and hence limits the clustering performance on social networks. To address this problem, a Similarity-based Multi-Prototype (SMP) community detection approach is proposed in this paper. In SMP, vertices in each community carry various weights to describe their degree of representativeness. This mechanism enables each community to be represented by more than one node. The centrality of nodes is used to calculate prototype weights, while similarity is utilized to guide us to partitioning the graph. Experimental results on computer generated and real-world networks clearly show that SMP performs well for detecting communities. Moreover, the method could provide richer information for the inner structure of the detected communities with the help of prototype weights compared with the existing community detection models