Semantics & Context

Everything we see, hear or touch in the realm of digital media has a specific form, meaning and function. Given a set of forms – be they visual elements of graphical interfaces, words or tangible objects – we are ultimately interested in their function as digital mediators between humans and computers. In order to examine the functioning of mediating forms one needs to look at both their semantics and the context in which they are being used. This constitutes our motivation for looking at semantic- and contextual computing as a closely intertwined research focus.

Semantic Computing

This research area examines the employment of semantic technologies for enabling digital media systems and interfaces to understand the user's intention, the digital content at hand and themselves. Correspondingly, research questions arise how to represent and determine the pertinent knowledge as well as how to employ the models -ranging from fully axiomatized ontologies to lightweight folksonomies. Specific areas of employment are, for example, searching, extracting and understanding digital content such as speech, text/hypertext or images.

Contextual Computing

Context is still a challenge for multimodal human computer interaction. The main-stream treatment language processing and human-computer interaction is based on the principle of strong compositionality and on representational approaches, these state that meaning is determined by form and is representable independent of context. Context is also problematic in the myriad practical applications of artificial intelligence. There is now increasing recognition that context-independent techniques are approaching their limits and more efforts are focusing on contextual computing in theory and practice.

Projects:

SmartWeb

In the SmartWeb project we aim to realize an intuitive mobile access to the Semantic Web by combining natural language processing with intelligent techniques from web search and web data analysis.

Knowledge Management (SFB 637 - B4)

In analogy to conventional logistics, autonomous logistic processes are in need of knowledge to perform their task. Data, information, and knowledge are the key resources which ensure the quality of the logistic process.

Publications: