Given a labeled graph containing fraudulent and legitimate nodes, which nodes group
together? How can we use the riskiness of node groups to infer a future label for new …

Background With the rapid accumulation of proteomic and genomic datasets in terms of
genome-scale features and interaction networks through high-throughput experimental …

Sensor networks, communication and financial networks, web and social networks are
becoming increasingly important in our day-to-day life. They contain entities which may …

Are investing activities dependent on social relationships? In our research, we apply social
network analysis to the field of investing behaviors and discover that investors have a …

Collective Classification (CC) is the process of simultaneously inferring the class labels of a
set of inter-linked nodes, such as the topic of publications in a citation graph. Recently …

Recently a number of modeling techniques have been developed for data mining and
machine learning in relational and network domains where the instances are not …

Recently, a number of modeling techniques have been developed for data mining and
machine learning in relational and network domains where the instances are not …

Collective classification (CC) is a task to jointly classifying related instances of network data.
Enabling CC usually improves the performance of predictive models on fully-labeled training …

This paper proposes a method to improve the identification effect of technical Trajectory by
adding ghost edges in the patent citation network, which includes calculating patent …

A new method of feature extraction in the social network for within-network classification is
proposed in the paper. The method provides new features calculated by combination of …