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 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...
The paper presents a framework for semi-supervised nonlinear embedding methods useful for exploratory analysis and visualization of spatio-temporal network data. The method provid...
A boosting algorithm based on cellular genetic programming to build an ensemble of predictors is proposed. The method evolves a population of trees for a fixed number of rounds an...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
In this paper, we discuss Conceptual Knowledge Discovery in Databases (CKDD) in its connection with Data Analysis. Our approach is based on Formal Concept Analysis, a mathematical ...
Joachim Hereth Correia, Gerd Stumme, Rudolf Wille,...