Answer Set Programming (ASP) is one of the most prominent and successful knowledge representation paradigms. The success of ASP is due to its expressive non-monotonic modeling language and its efficient computational methods originating from building propositional satisfiability solvers. The wide adoption of ASP has motivated several extensions to…

The Dublin Core "1:1 Principle" asserts that "related but conceptually different entities, for example a painting and a digital image of the painting, are described by separate metadata records" (Woodley et al., 2005). While this seems to be a simple requirement, studies of metadata quality have found that cultural heritage…

Scientists produce research resources that are useful to future research and innovative efforts. In a typical scientific scenario, the results created by a collaborative team often include numerous artifacts, observations and relationships relevant to research findings, such as programs that generate data, parameters that impact outputs, workflows…

Because many words of a language have more than one meaning, readers regularly need to disambiguate words during sentence comprehension. Using priming, eye-tracking, and event-related brain potentials, this thesis tested whether readers differently disambiguate words with semantically related meanings like "wire" and "cone,"…

Social media provide a multitude of opportunities for knowledge contribution and sharing. However, the content reliability issue has caused comprehensive attention, especially on credible social media, such as Wikipedia. Despite Wikipedia's success with the open editing model, dissenting voices give rise to unreliable content due to two…

The study addresses the automated translation of architectural drawings from 2D Computer Aided Drafting (CAD) data into a Building Information Model (BIM), with emphasis on the nature, possible role, and limitations of a drafting language Knowledge Representation (KR) on the problem and process. The central idea is that CAD to BIM translation is a…

The deep semantic understanding necessary for complex natural language processing tasks, such as automatic question-answering or text summarization, would benefit from highly accurate word sense disambiguation (WSD). This dissertation investigates what makes an appropriate and effective sense inventory for WSD. Drawing on theories and…