Christian Seeling

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A large amount of strategically relevant business information is contained in unstructured texts. While information brokering approaches are used to contextualize such documents and to generate metadata, text mining is used to explore large document spaces. So far, little attention has been paid on a value-adding combination of these technologies. In this(More)
Analyzing, structuring and organizing documented knowledge is an important aspect of knowledge management. In order to ease the access to text collections, in literature so-called document maps have been proposed which visualize the inherently vague semantic similarity structure of a corpus of documents. In this paper we investigate a document map system(More)
Visualization interfaces that offer multiple coordinated views on a particular set of data items are useful for navigating and exploring complex information spaces. In this paper we address the problem of mining text information which is associated with structured data from relational data sources. We present a multi-view paradigm that closely integrates(More)
This work presents an extensible architecture for fully-automated long-term monitoring of documents on the web. The framework enables easy coupling of existing search services of different kind, making the approach suitable for mixed environments (e.g. classic web and semantic web).The proposed architecture supports a process for repeated querying and(More)
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