Professional Homepage of Prof. Dr. Michael Granitzer (Under Construction)

Welcome to my professional homepage, which gathers all activities and resources of my past and current research.

"The prize is the pleasure of finding the thing out, the kick in the discovery, the observation that other people use it - those are the real things, the honors are unreal to me." (R. Feynman about the nobel prize)

Short CV

Since 2017 I am holding the Chair of Data Science at the University of Passau, following a Professorship for Media Computer Science since 2012 (also at University of Passau). Before, I was Scientific Director of the Know-Center Graz (since 2010) and assistant professor at the Knowledge Technology Institute of Graz University of Technology (since 2008). In 2011, I had the pleasure to visit Mendeley Ltd as a Marie Curie Research Fellow working on machine learning and information retrieval in academic knowledge bases.

On my educational background: I studied Telematik at Graz University of Technology with special focus on Computational Intelligence and Biomedical Computer Science. After receiving my MsC in 2004 I obtained a PhD degree, passed with distinction, in technical science in 2006 under the supervision of Prof. Klaus Tochtermann and Prof. Hermann Maurer. In parallel to my MsC and PhD studies, I worked as R&D project manager and later as division manager for Knowledge Discovery at the Know-Center Graz (2001-2010), where I conducted and managed projects on automatic text classification, text retrieval in millions of documents and visualisation of several million documents. Before this, I was involved in several database projects at JOANNEUM RESEARCH Austria in particular the development of the IMDAS platform for museums and libraries.

Research Interests

The on-going data deluge has been the main driver for my research. I am particularly interested in intelligent methods for extracting knowledge from unstructured or semi-structured media (e.g. text, images, social media, linked data) through exploiting synergies between man and machine

Research Fields:

• Knowledge Discovery in Media with a focus on Deep Learning Methods
• Visual Analytics
• (Social) Network Analysis
• Personalized Information Retrieval

Social Media Profiles

With varying degree of completness

• ORCID
• Google Scholar
• LinkedIn
• Xing
• Mendeley
• Research Gate
• Twitter
• GitHub

Selected Publications

All Publications

European Projects

EU FP7 IP EEXCESS - Enhancing Europe’s eXchange in Cultural Educational and Scientific reSources.
Scientific Coordinator (2013-2016)
The vision of EEXCESS is to push high-quality content from the so-called long tail to platforms and devices which are used every day. Instead of navigating a multitude of libraries, repositories and databases, users will find relevant and specialised information in their habitual environment.

FP7 STREP CODE - Commercially Empowered Linked Open Data Ecosystems in Research
Scientific Coordinator (2012-2014)
The vision of CODE has been to create data markeptlace concept for research through mining facts from research papers and integrating those facts into Linked Open Data repositories. Crowdsourcing workflows have been investigated in order to enhance the quality of fact extraction.

FP7 STREP MICO - Media In COntext
(2013-2016)
MICO will develop models, standards and software tools to jointly analyse, query and retrieve information out of connected and related media objects (text, image, audio, video, office documents) to provide better information extraction results for more relevant search and information discovery.

FP7 Marie Curie IAPP Project TEAM -Transferring knowledgE in Academic knowledge
Coordinator (2010-2012)
The main objective of the TEAM proposal is to enable and cultivate a dynamic partnership and two-way transfer of knowledge between TUG as a public research institution with key competencies in knowledge management and semantic technologies and the two private commercial SMEs Mendeley and ELIKO with engineering expertise in developing commercial knowledge management solutions and products

Eurostars Project MAKIN IT-Managing Academic Knowledge with INtegrated, collaboratIve Tools
Researcher, (2009-2010)
The general objective of the MAKIN’ IT project is to develop a consistent database of academic knowledge, driven by semantic algorithms, to efficiently manage and share academic content, and to achieve superior recommendations based on personalised user profiles and user preferences.

FP7 Marie Curie IRSES Project WIQ EI–Web Information Quality Evaluation Initiative
Coordinator, (2011-2012)
Today’s information and data pools on the Web focus on the quantity of information rather than its quality; a fact observable through the increasing size of the blogosphere, the number of growing artificially created data, the well established copy & paste syndrome and the lack of semantically enriched data. The research underlying WIQ-EI’s knowledge transfer addresses information quality in terms of determining web quality measures and the development of multi-lingual, automatic methods for estimating those measures.

Nationaly funded research Projects - Germany

BMBF funded VIP Project mirKUL - Kollaborative Unterstützung von Arbeits- und Lernprozessen im Unternehmen mit mobilen interaktiven Multimedia-Anwendungen
Scientific Coordinator, (2013-2016)
(in German:) Ziel des vorliegenden Validierungsvorhabens mirKUL ist es, kleinen und mittleren Unternehmen (KMU) ein kostengünstiges, multimedial gestütztes System zum Wissenstransfer anzubieten, dass sich an die speziellen Bedürfnisse des Unternehmens anpassen lässt und die rechtlichen Anforderungen des Datenschutzes und des Betriebsverfassungsrechts erfüllt. Die wirtschaftlichen Verwertungsmöglichkeiten sollen bei unternehmensinternen, unternehmensexternen und unternehmens- übergreifende Anwendungen überprüft werden. Im Erfolgsfall entstehen neue Dienstleistungen und Softwareprodukte, mit denen die Effizienz des Wissensmanagements in KMU nachhaltig gesteigert werden kann.

Internetkompetenzzentrum Ostbayern: Teilprojekt BODA - Big and Open Data Analytics für den Mittelstand
Scientific Coordinator, (2015-2020)
(in German:) Das Teilprojekt „BODA“ zielt auf die Erforschung, Entwicklung und prototypische Erprobung neuer Cloud-Dienste zur Nutzbarmachung offener Daten in Big Data-Prozessen für den bayerischen Mittelstand. Die Erforschung erfolgt in Zusammenarbeit mit Wirtschaftspartnern u.a. aus dem Bereich der Datenanalyse und Anwendungspartnern im Bereich der datengestützten Kundenanalyse.

IT4ALL: Digitale Geisteswissenschaften Bayern
Teaching Project, Coordinator, (2015-2020)

National funded research Projects - Austria

Different K-Plus/COMET Projects at the Know-Center GmbH in Graz
Several Roles, (2001-2012)
(in German:) K-Plus/COMET projects are application oriented research projects conducted at the Know-Center Graz, where I have been area manager and later on scientific director. The research projects were funded under the Austrian K-Plus/COMET program. Partner projects have been conducted with industry partners; strategic research projects are basic research projects conducted with scientific partners.

DYONIPOS - DYnamic ONtology based Integrated Process OptimiSation
Scientific Coordinator, (2006-2008)
(in German:) Zielsetzung von DYONIPOS ist die Entwicklung eines kontextsensitiven, intelligenten, hochflexiblen Systems, welches zu einer signifikanten Produktivitätssteigerung in wissensintensiven Unternehmen beiträgt. Basierend auf semantischen Technologien, Methoden des Knowledge Discovery und Verfahren wie der Wissensflussanalyse integriert DYONIPOS strukturierte, explizit abgebildete Geschäftsprozesse und dynamische, undokumentierte Wissensflüsse. Semantische Technologien ermöglichen dabei eine flexible und einheitliche Behandlung von strukturierten als auch unstrukturierten Geschäftsprozessen und Daten.

FIT-IT Semantic Systems: MISTRAL- Measurable Intelligent and Reliable Semantic Extraction and Retrieval of Multimedia Data
Researcher, (2005-2007)
Multimedia data has a rich and complex structure in terms of inter- and intra-document references and can be an extremely valuable source of information. However, this potential is severely limited until and unless effective methods for semantic extraction and semantic-based cross-media exploration and retrieval can be devised. MISTRAL will extract a large variety of semantically relevant metadata from one media type and integrate it closely with semantic concepts derived from other media types. Eventually, the results from this cross-media semantic integration will also be fed back to the semantic extraction processes of the different media types so as to enhance the quality of the results of these processes.