In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
There has historically been very little concern with extrapolation in Machine Learning, yet extrapolation can be critical to diagnose. Predictor functions are almost always learne...
Many social Web sites allow users to annotate the content with descriptive metadata, such as tags, and more recently to organize content hierarchically. These types of structured ...
Anon Plangprasopchok, Kristina Lerman, Lise Getoor
Abstract. User generated content in general, and blogs in particular, form an interesting and relatively little explored domain for mining knowledge. We address the task of blog di...
Wouter Weerkamp, Krisztian Balog, Maarten de Rijke
The authors of topic map-based learning resources face major difficulties in constructing the underlying ontologies. In this paper we propose two approaches to address this problem...