Inhalt des Dokuments
Termine Forschungskolloquium DIMA
Termin/Ort | Dozent/Them |
---|---|
Mo. 13.07.2009 16.00 c.t. DIMA | Stephan Kliche "Folksonomy based data standardization" |
entfaellt Mi. 08.07.2009 16.00 c.t. DIMA | Prof. Dr.
Herbert Weber Fraunhofer ISST, Berlin "Das THESEUS-Forschungsprogramm Der Bundesregierung" |
Mo. 06.07.2009 16..00 c.t. DIMA | Cristian Hein und Michael Wagner Fraunhofer FOKUS Berlin "Das ModelBus Repository" |
Mo. 15.06.2009 16.00 c.t. DIMA | Prof. Andras Pataricza Budapest University of Technology and Economics, Hungary and: Center for Advanced Security Research Darmstadt, Germany "The evolving model engineering: from feasibility studies to production technology" |
Mo. 25.05.2009 16.00 c.t. DIMA | Isabel Drost neofonie GmbH Berlin Mahout - Scaling Machine Learning |
Di. 17.03.2009 14.00 c.t. DIMA | Dr. Ulf Brefeld TU Berlin, FG Maschinelles Lernen "Machine Learning Approaches to Finding Relations in Natural Language" |
Stephan Kliche
Abstract:
"Folksonomy based data standardization"
Feed
Mashups integrate different Web 2.0 data sources. In this area one has
to deal with common data integration problems such as in ETL and EII.
The problem with web based data integration is that data sources often
lack in structure. Furthermore entities in data sources have different
representations for the same domain.
IBM MashupHub is a
situational application environment helping “business users” to
create Mashups. Those users often have problems to integrate their
data because they don’t know the common touch points of their data
sources.
The solution presented in this talk makes use of
folksonomy in enterprises. We claim that there are some expert users
who might know how to join domains and there are different
standardization services in the web or the company’s intranet.
The system we discuss is able to analyze Mashups created by those
users and store the information in a repository. Furthermore it is
able to give suggestions on how to integrate unknown data
sources.
Prof. Dr. Herbert Weber, Fraunhofer ISST, Berlin
Abstract:
THESEUS ist ein Programm und ein sogenanntes
Leuchtturmprojekt der Bundesregierung. An THESEUS sind mehr als 30
Partner beteiligt. Die Präsentation des Projektes wird Ausgangspunkt
für die Beschreibung der Aufgaben der sogenannten Begleitforschung
sein. Dies wird kein primär technischer Vortrag, sondern - so habe
ich den Wunsch von Herrn Kollegen Markl verstanden - ein
"förderpolitischer" Vortrag. Technische Fragen werden
selbstverständlich, wo immer nötig, eine Rolle
spielen.
Cristian Hein und Michael Wagner, Fraunhofer FOKUS, Berlin
Short
Abstract:
Das ModelBus Repository ist ein Model
Repository, welches im Kontext
von Förderprojekten von
Fraunhofer FOKUS entwickelt wird. Es ist
zentraler Bestandteil
der ModelBus Architektur, welche die verteilte
modellgetriebene
Entwicklung unterstützen soll. Vorgestellt werden die
Architektur, Funktionalität und Zukunft des Repositories und
Eclipse
Team Providers.
Short
Bio:
Cristian Hein und Michael Wagner sind die beiden
Hauptentwickler des
ModelBus. Beide haben ihr Diplom an der
TU-Berlin gemacht, und arbeiten
seit mehreren Jahren für
Fraunhofer FOKUS als Forscher im Bereich der
modellgetriebenen
Softwareentwicklung und Automatisierung.
Prof. Andras Pataricza, Budapest University of Technology and Economics, Hungary and: Center for Advanced Security Research Darmstadt, Germany
Abstract:
The paradigm
of model-driven system design rapidly dominates software
system
engineering. The core element of all model-based technologies
is
model transformation, which serves for mapping an engineering model
into mathematical representation for analysis or into a run-time
code.
Despite of the fact that transformers play a similarly
central role in
the efficiency, quality and practical usability
of MDA, as compilers
do it in traditional software engineering,
transformation based model
engineering is still in its very
initial and premature state.
The talk summarizes the main
conclusions gained in a series of European
projects at the
Budapest University of Technology and Economics and
Optxware
Ltd. in different fields of application of model transformations,
including tool and data integration, automated generation of
safety-critical
system architectures, derivation of validation
and validation models and
workflows for certification. In
particular, it addresses the aspects of
(1) traceability, (2)
rapid transformation development, (3) scalability
approaches for
large models, (4) adaptivity of transformations with a
special
emphasis to domain specific languages, (5) model and transformation
complexity and quality assessment.
Bio:
Professor András Pataricza
received his diploma in Electrical Engineering
in 1977 from the
Technical University Budapest, his PhD and Doctor of the
HungarianAcademy of Sciences degree in 1988 and 2008, respectively.
Since 1977 he is with the Department of Measurement and
Information Systems.
He is the leader of the Fault-Tolerant
Systems Research Group.
He was a visiting professor at the
University of Erlangen-Nuremberg
between 1993 and 1994, and in
2003.
He is the author, co-author or editor of 13 books, 7 book
chapters,
25 journal articles and 110 conference papers.
He has been the Hungarian project leader of several EU projects
(HIDE,
HIDENETS, RESIST, SENSORIA, GENESYS and DECOS) and many
academic and
industrial research projects. He was PC member of
DSN, EDCC, DDECS, ISAS,
FTCS etc. conference series and SC
member, general co-chair and program
co-chair of EDCC, ISAS and
DDECS conference series. He is founder and
president of a
spin-off company named OptXware established together with
the
members of his Research Group in order to promote model-based
computing
with a special emphasis of the aspects and
consolidation of dependability.
Isabel Drost, neofonie GmbH Berlin
Abstract
Mahout ist
ein Apache Projekt unter der Schirmherrschaft von Lucene.
Das
Ziel von Mahout ist es, skalierbare, Apache lizensierte Machine
Learning Bibliotheken zur Verfügung zu stellen. Der Vortrag wird
einen Überblick über das Projekt geben: Nachdem kurz auf den
Hintergrund des Projektes eingegangen wurde, werden die bisher
verfügbaren Algorithmen knapp vorgestellt sowie auf zukünftige
Entwicklungen eingegangen.
Bio
Isabel Drost ist Organisator des
Apache Hadoop Get Together in Berlin.
Sie ist Cogründer von und
Committer bei Apache Mahout. Isabel arbeitet
für die neofonie
GmbH Berlin. Nachdem sie ihr Diplom von der Hochschule
für
Technik und Wirtschaft Mittweida erlangt hat, arbeitete sie als
wissenschaftlicher Mitarbeiter an der HU und war für sechs Monate
bei
Google Zürich als Praktikant angestellt.
Dr. Ulf Brefeld, TU Berlin, FG Maschinelles Lernen
Abstract
Semantic
processing of natural language is one of the oldest problems in
machine learning and still far from being solved. By now, low-level
tasks
including part-of-speech tagging and named entity
recognition are well
understood while complex tasks such as
parsing, machine translation, and
sentiment prediction are still
lively subjects of ongoing research. The
talk focuses on the
identification of relations in sentences. Starting
from classical
(pipelined) approaches we'll derive state-of-the-art
techniques
by addressing complex tasks in a single optimization problem.
We'll also learn about two naturally arising problems: Firstly, the
trade-
off between performance and execution time and secondly,
the quest for
annotated data.
Bio
Since October 2007, Ulf is a postdoc
in the Machine Learning Group at
Technische Universität Berlin.
Prior to joining TU Berlin, he worked at
Max Planck Institute for
Computer Science in Saarbrücken and at Humboldt-
Universität zu
Berlin. Ulf received a Diploma in Computer Science in 2003
from
Technische Universität Berlin and a Ph.D. (Dr. rer. nat.) in 2008
from Humboldt-Universität zu Berlin.