In this paper, we propose a socioscope model for social-network and human-behavior
analysis based on mobile-phone call-detail records. Because of the diversity and complexity …

Heterogeneous networks are networks consisting of different types of objects and links. They
can be found in several fields, ranging from the Internet to social sciences, biology …

This paper describes a general framework for learning Higher-Order Network Embeddings
(HONE) from graph data based on network motifs. The HONE framework is highly …

As the complexity of data increases, so does the importance of powerful representations,
such as relational and logical representations, as well as the need for machine learning …

Within-network classification, where the goal is to classify the nodes of a partly labeled
network, is a semi-supervised learning problem that has applications in several important …

Link prediction is a key problem in the field of undirected graph, and it can be used in a
variety of contexts, including information retrieval and market analysis. By “undirected …

The massive spread of social networks provided a plethora of new possibilities to
communicate and interact worldwide. On the other hand, they introduced some negative …

Link prediction is the problem of detecting missing links or predicting future link formation in
a network. Application of link prediction to social media, such as Twitter and Facebook, is …

Ensemble classification methods that independently construct component models (eg,
bagging) improve accuracy over single models by reducing the error due to variance. Some …