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WeKnowIt - Emerging, Collective Intelligence for personal, organisational and social use

In den letzten Jahren wurden immense Fortschritte im Bereich der Kommunikationstechnologie und besonders bei mobilen Endgeräten und Web-Technologien erzielt. Deshalb ist es heutzutage für (private) Nutzer und Organisationen einfach, Inhalte zu erzeugen und zu verteilen. Jedoch erreichen solche digitalen Inhalte schnell eine Anzahl, die es kompliziert und kostspielig macht, in ihnen relevante Informationen wiederzufinden. Das Ziel von WeKnowIt is es deshalb, neue Techniken zu entwickeln, die Wissen auf mehreren Ebenen aus den Nutzer-Inhalten herausfiltern. Dabei entsteht kollektives Wissen aus der Zusammenarbeit von vielen Individuen. Inhalte aus verschiedensten Quellen werden analysiert und kombiniert: aus digitalen Inhalten und kontextueller Information (medialem Wissen), aus Feedback-Informationen von Nutzern (Massenwissen) und aus sozialen Interaktionen von Nutzern (soziales Wissen). Diese Wissensformen sollen genutzt werden, damit sowohl End-Nutzer und Organisationen davon profitieren können. Die automatische Generierung kollektiven Wissens stellt eine Weiterentwicklung von traditionellen Methoden zur Informationsverteilung dar, weil z.B. die semantische Analyse die Inhalte selbst sowie den sozialen Kontext analysieren muss. WeKnowIt wird in zwei verschiedenen Fallstudien die breitgefächerte Anwendbarkeit seiner Ergebnisse zeigen: Eine Fallstudie beschäftigt sich dabei mit der Bearbeitung von Notfällen und die andere Fallstudie beschäftigt sich mit einer Verbrauchergruppe.

Laufzeit

  • TBD

Geldgeber

  • EU, Information Society Technologies (IST)

Partner

  • CENTRE FOR RESEARCH AND TECHNOLOGY HELLAS
  • Lycos Europe GmbH
  • Motorola Ltd
  • The University of Sheffield
  • Universität Karlsruhe (TH)
  • Vodafone Panafon Hellenic
  • Telecommunications company S.A.
  • Software Mind Sp. z o.o.
  • Sheffield City Council

Projekt Homepage

Prof. Dr. Steffen Staab

B 108
+49 261 287-2761
staab@uni-koblenz.de

Short CV

I have studied computer science and computational linguistics at the Universität Erlangen-Nürnberg and at the University of Pennsylvania. I worked in the previous computational linguistics research group at the Universität Freiburg and did my Ph.D. in computer science in the faculty for technology in 1998. Afterwards I joined Universität Stuttgart, Institute IAT & Fraunhofer IAO, before I moved on to the Universität Karlsruhe (now: KIT), where I progressed from project lead, over lecturer and senior lecturer and did my habilitation in 2002. In 2004 I became professor for databases and information systems at Universität Koblenz-Landau, where I founded the Institute for Web Science and Technologies (WeST) in 2009. In parallel, I hold a Chair for Web and Computer Science at University of Southampton since March 2015.

Research Interests

Data represent the world on our computers. While the world is very intriguing, data may be quite boring, if one does not know what they mean. I am interested in making data more meaningful to find interesting insights in the world outside.

How does meaning arise?

  • One can model data and information. Conceptual models and ontologies are the foundations for knowledge networks that enable the computer to treat data in a meaningful way.
  • Text and data mining as well as information extraction find meaningful patterns in data (e.g. using ontology learning of text clustering) as well as connections between data and its use in context (e.g. using smartphones). Hence, knowledge networks may be found in data.
  • Humans communicate information. In order to understand what data and information means, one has to understand social interactions. In the context of social network knowledge networks become meaningful for human consumption.
  • Eventually meaning is nothing that exists in the void. Data and information must be communicated to people who may use insights into data and information. Interaction between humans and computers must happen in a way that matches the meaning of data and information.

The World Wide Web is the largest information construct made by mankind to convey meaningful data. Web Science is the discipline that considers how networks of people and knowledge in the Web arise, how humans deal with it and which consequences this has for all of us. The Web is a meaning machine that I want do understand by my research.

Where else you might find me?

In my office (room B110), traveling, running in the local forest or in Changa or at AHS. Watch out! 

Prof. Dr. Dr. Sergej Sizov

sizov@uni-koblenz.de

Felix Schwagereit

B 314
+49 261 287-2709
schwagereit@uni-koblenz.de

I am a PhD Student in the WeST intitute. I have worked in the previous projects SOAinVO (BMBF), WeKnowIt (EU) und ROBUST (EU). My main resarch topic are online communities. I was prevously active in the fields of distributed communities, Policy Models, Semantic Web and Linked Open Data. Currently I am active in resarch on simulation of macro dynamics of online communities.

In my freetime I like to row on the river Mosel as well as to explore the nice landscape around Koblem by foot.