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Zeit: Montag, 06.08.2018, 14.00 Uhr
Ort:: Seminarraum 5053.2 (B-IT Research School, ggü. AH 6)
Referent: Herr Erion Elmasllari, M.Sc.
Titel: A Framework for the Successful Design and Deployment of Electronic
Triage Systems
Abstract:
Triage -- the prioritisation of victims by emergency of treatment -- suffers
from various well-known problems that impact victims' survival chances. Many
electronic triage systems have been proposed as a solution, but none of them
have been accepted by emergency responders. Furthermore, the reasons for the
rejection have never been satisfyingly analyzed until now.
The dissertation identifies key criteria for the acceptance of electronic
triage systems and presents a conceptual framework, targeted at system
designers, to actively guide them towards well-accepted e-triage
implementations. An example implementation based on the framework is
designed, implemented, and evaluated in large-scale trials, followed by a
retrospective, higher-level look on the limits, risks, and intrinsic issues
of introducing ICT support in triage.
Es laden ein: Die Dozenten der Informatik
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Zeit: Wednesday, August 1st 2018, 10:00am
Ort: Informatik E3, Room 9222
Referent: Dipl.-Inform. Matthias Huck
Titel: Statistical Models for Hierarchical Phrase-based Machine Translation
Abstract:
Machine translation systems automatically translate texts from one natural
language to another. The dominant approach to machine translation has been
phrase-based statistical machine translation for many years. In statistical
machine translation, probabilistic models are learned from training data, and a
decoder is conducting a search to determine the best translation of an input
sentence based on model scores. Phrase-based systems rely on elementary
translation units that are continuous bilingual sequences of words, called
phrases.
The hierarchical approach to statistical machine translation allows for phrases
with gaps. Formally, the hierarchical phrase inventory can be represented as a
synchronous context-free grammar that is induced from bilingual text, and
hierarchical decoding can be carried out with a parsing-based procedure. The
hierarchical phrase-based machine translation paradigm enables modeling of
reorderings and long-distance dependencies in a consistent way. The typical
statistical models that guide hierarchical search are fairly similar to those
employed in conventional phrase-based translation.
In this work, novel extensions with statistical models for hierarchical
phrase-based machine translation are developed, with a focus on methods that do
not require any syntactic annotation of the data. Specifically, enhancements
of hierarchical systems with extended lexicon models that take global source
sentence context into account are investigated; various lexical smoothing
variants are examined; reordering extensions and a phrase orientation model for
hierarchical translation are introduced; word insertion and deletion models are
presented; techniques for training of hierarchical translation systems with
additional synthetic data are suggested; and a training method is proposed that
utilizes additional synthetic data which is created via a pivot language.
The beneficial impact of the extensions on translation quality is verified by
means of empirical evaluation on various language pairs, including
Arabic-English, Chinese-English, French-German, English-French, and
German-French.
Es laden ein: Die Dozenten der Informatik
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Stephanie Jansen
Faculty of Mathematics, Computer Science and Natural Sciences
HLTPR - Human Language Technology and Pattern Recognition
RWTH Aachen University
Ahornstraße 55
D-52074 Aachen
Tel. Frau Jansen: +49 241 80-216 06
Tel. Frau Andersen: +49 241 80-216 01
Fax: +49 241 80-22219
sek(a)i6.informatik.rwth-aachen.de
www.hltpr.rwth-aachen.de
Tel: +49 241 80-216 01/06
Fax: +49 241 80-22219
sek(a)i6.informatik.rwth-aachen.de
www.hltpr.rwth-aachen.de