In the traditional link prediction problem, a snapshot of a social network is used as a starting point to predict, by means of graph-theoretic measures, the links that are likely ...
Vincent Leroy, Berkant Barla Cambazoglu, Francesco...
Compressing social networks can substantially facilitate mining and advanced analysis of large social networks. Preferably, social networks should be compressed in a way that they...
Users’ behaviors (actions) in a social network are influenced by various factors such as personal interests, social influence, and global trends. However, few publications sys...
Chenhao Tan, Jie Tang, Jimeng Sun, Quan Lin, Fengj...
We propose an online topic model for sequentially analyzing the time evolution of topics in document collections. Topics naturally evolve with multiple timescales. For example, so...
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
Mining cluster evolution from multiple correlated time-varying text corpora is important in exploratory text analytics. In this paper, we propose an approach called evolutionary h...
Memory leaks are caused by software programs that prevent the reclamation of memory that is no longer in use. They can cause significant slowdowns, exhaustion of available storag...
Existing cost-sensitive learning methods work with unequal misclassification cost that is given by domain knowledge and appears as precise values. In many real-world applications,...
An ensemble is a set of learned models that make decisions collectively. Although an ensemble is usually more accurate than a single learner, existing ensemble methods often tend ...
In this paper we introduce a modular, highly flexible, opensource environment for data generation. Using an existing graphical data flow tool, the user can combine various types...