The 1st Workshop on Interacting with Information Networks, IIN 2009, will take place October, 2nd during INFORMATIK 2009 at the Faculty of Computer Science of the University of Lübeck, Germany.
Due to only a small number of submissions, the workshop has been cancelled. Please consider to participate at the "Workshop on explorative Analytics of Information Networks" at ECML/PKDD 2009: http://www.inf.uni-konstanz.de/EIN2009
Relations between objects in large information ar-chives can be represented as a mesh of connected information entities. These relations could, for example, model explicit cross references based on html links or citations, keywords or named entities connecting two objects like a drug name appearing in a lab report and a scientific paper, or vague cross references indicating a content based similarity between text documents. Analyzing such networks in order to retrieve, discover or even create new connections that are yet unknown requires powerful tools for visualization, interaction and mining. While many graph mining tools have already been developed there is a lack of integrated tools that enable a user to interact with huge information networks such that creative information discoveries can be supported. Besides refined mining and aggregation methods the interaction with the mesh itself requires sophisticated visualization methods that have to consider the limited amount of information a user is able to handle at the same time. Therefore the goal of this workshop is to bring together experts from computer science (especially data mining, information visualization and human computer interaction), mathematics as well as cognitive psychology to intensify the exchange of ideas between the different research communities involved, in order to enable the development of advanced tools for creation, analysis and visualization of complex information networks.
Participants
The workshop focuses especially on researchers that are working on methods for representation of complex knowledge resources, (dynamic) data analysis methods, semantic and other information networks, and visualization methods as well as user interface design.
