Exposing multi-relational networks to single-relational network analysis algorithms

@article{Rodriguez2010ExposingMN,
  title={Exposing multi-relational networks to single-relational network analysis algorithms},
  author={Michael A. Rodriguez and Joshua Shinavier},
  journal={ArXiv},
  year={2010},
  volume={abs/0806.2274}
}
Predicting Links in Multi-relational Networks
TLDR
A novel method for link prediction in multi-modal and multi-relational networks based on semantics of simple and compound relationships in the given network, i.e., a compound relationship represents a well-defined pattern of simple relationships between two typed nodes in the network.
SQNR: A System for Querying Nodes and relations in multi-relational social networks
TLDR
A system to query nodes that interact frequently in the specified relationships and to query relationships in which the specified community patterns can be satisfied, which provides new insights about relationships amongst actors are developed.
Community Detection in Multi-relational Social Networks
TLDR
This paper introduces a novel co-ranking framework, named MutuRank, that makes full use of the mutual influence between relations and actors to transform the multi-relational network to the single- Relational network.
Discovering Communities in Multi-relational Networks
TLDR
This chapter gradually explores the research into discovering communities from MRNs by introducing the generalized modularity of the MRN, which paves the way for applying modularity optimization-based community detection methods on MRNs.
Chapter 4 Discovering Communities in Multi-relational Networks
TLDR
This chapter gradually explores the research into discovering communities from MRNs by introducing the generalized modularity of the MRN, which paves the way for applying modularity optimization-based community detection methods on MRNs.
Detecting overlapping communities in poly-relational networks
TLDR
This paper attempts to relax this strong assumption that different relations are independent from each other by introducing a novel co-ranking framework, named MutuRank, and presents a novel GMM-NK (Gaussian Mixture Model with Neighbor Knowledge) algorithm incorporating the impact from neighbors into the traditional GMM.
User-Dependent Multi-relational Community Detection in Social Networks
TLDR
This paper proposes a user-dependent method to detect communities in multi-relational social networks using Normalized mutual information (NMI) between the desirable set of communities and the sets of communities detected in each single- Relational graph as the weights for measuring the importance of all kinds of relationship types.
A Systematic Survey on Multi-relational Community Detection
TLDR
This study is the most comprehensive survey dedicated to multi-relational networks community detection, and divides the considered models into two main groups: direct methods and indirect methods.
Modeling Topic Diffusion in Multi-Relational Bibliographic Information Networks
TLDR
Two variations of the linear threshold model for multi-relational networks are proposed, by considering the aggregation of information at either the model level or the relation level, and can determine the diffusion power of each relation type, which helps to understand the diffusion process better in the multi- Relational bibliographic network scenario.
Learning Collective Behavior in Multi-relational Networks
TLDR
This dissertation proposes two classification frameworks for identifying human collective behavior in multi-relational social networks and unsupervised and supervised learning models for relationship prediction in multi -relational collaborative networks that improve the performance of homogeneous predictive models by differentiating heterogeneous relations and capturing the prominent interaction patterns underlying the network structure.
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