Link prediction in complex networks: A survey
L Lü, T Zhou - Physica A: statistical mechanics and its applications, 2011 - Elsevier
Link prediction in complex networks has attracted increasing attention from both physical
and computer science communities. The algorithms can be used to extract missing …
and computer science communities. The algorithms can be used to extract missing …
Gmnn: Graph markov neural networks
This paper studies semi-supervised object classification in relational data, which is a
fundamental problem in relational data modeling. The problem has been extensively studied …
fundamental problem in relational data modeling. The problem has been extensively studied …
Structural-rnn: Deep learning on spatio-temporal graphs
Abstract Deep Recurrent Neural Network architectures, though remarkably capable at
modeling sequences, lack an intuitive high-level spatio-temporal structure. That is while …
modeling sequences, lack an intuitive high-level spatio-temporal structure. That is while …
Graph based anomaly detection and description: a survey
Detecting anomalies in data is a vital task, with numerous high-impact applications in areas
such as security, finance, health care, and law enforcement. While numerous techniques …
such as security, finance, health care, and law enforcement. While numerous techniques …
Mining the Semantic Web: Statistical learning for next generation knowledge bases
Abstract In the Semantic Web vision of the World Wide Web, content will not only be
accessible to humans but will also be available in machine interpretable form as ontological …
accessible to humans but will also be available in machine interpretable form as ontological …
Mining heterogeneous information networks: a structural analysis approach
Most objects and data in the real world are of multiple types, interconnected, forming
complex, heterogeneous but often semi-structured information networks. However, most …
complex, heterogeneous but often semi-structured information networks. However, most …
[PDF][PDF] Probabilistic Graphical Models: Principles and Techniques
D Koller - 2009 - kobus.ca
A general framework for constructing and using probabilistic models of complex systems that
would enable a computer to use available information for making decisions. Most tasks …
would enable a computer to use available information for making decisions. Most tasks …
[图书][B] Mining heterogeneous information networks: principles and methodologies
Real world physical and abstract data objects are interconnected, forming gigantic,
interconnected networks. By structuring these data objects and interactions between these …
interconnected networks. By structuring these data objects and interactions between these …
[图书][B] An introduction to social network data analytics
CC Aggarwal - 2011 - Springer
The advent of online social networks has been one of the most exciting events in this
decade. Many popular online social networks such as Twitter, LinkedIn, and Facebook have …
decade. Many popular online social networks such as Twitter, LinkedIn, and Facebook have …