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We describe our approach for the extraction of drug-drug interactions from literature. The proposed method builds majority voting ensembles of contrasting machine learning methods, which exploit different linguistic feature spaces. We evaluated our approach in the context of the DDI Extraction 2011 challenge, where using document-wise cross-validation, the(More)
The most important way of conveying new findings in biomedical research is scientific publication. Extraction of protein-protein interactions (PPIs) reported in scientific publications is one of the core topics of text mining in the life sciences. Recently, a new class of such methods has been proposed - convolution kernels that identify PPIs using deep(More)
The extraction of protein-protein interactions (PPIs) reported in scientific publications is one of the most studied topics in Text Mining in the Life Sciences, as such algorithms can substantially decrease the effort for databases curators. The currently best methods for this task are based on analyzing the dependency tree (DT) representation of sentences.(More)
Traffic flow can be considered as a hybrid system which is characterized by two major behaviours: continuous ones in motorways and discrete ones in road junctions. We propose a modelling approach based on Petri nets. For this purpose, places of Petri nets stand for the road sections and transitions describe the flow between two consecutive sections and at(More)
Research results are primarily published in scientific literature and curation efforts cannot keep up with the rapid growth of published literature. The plethora of knowledge remains hidden in large text repositories like MEDLINE. Consequently, life scientists have to spend a great amount of time searching for specific information. The enormous ambiguity(More)
The BioCreative IV CHEMDNER Task provides participants with the opportunity to compare their methods for chemical named entity recognition (NER) and indexing in a controlled environment. We contributed to this task with our previous conditional random field based system [1] extended by a number of novel general and domain-specific features. For the latter,(More)
Simulation is often used for the evaluation of a Master Production Schedule (MPS). Also, the goal of this paper is the study of the design of a simulation model by reducing its complexity. According to theory of constraints, we want to build reduced models composed exclusively by bottleneck and, in order to do that, a neural network, particularly a(More)