Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
This paper describes a novel approach towards the empirical approximation of discourse relations between different utterances in texts. Following the idea that every pair of event...
How to efficiently discard potentially uninteresting rules in exploratory rule discovery is one of the important research foci in data mining. Many researchers have presented algor...
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...
Abstract: In the automotive and aerospace industry, millions of technical documents are generated during the development of complex engineering products. Particularly, the universa...