Refine
Year of publication
- 2013 (23) (remove)
Document Type
- Doctoral Thesis (10)
- Bachelor Thesis (4)
- Part of Periodical (4)
- Master's Thesis (2)
- Conference Proceedings (1)
- Diploma Thesis (1)
- Habilitation (1)
Language
- English (23) (remove)
Keywords
- Pflanzenschutzmittel (3)
- ABox (1)
- Abduktion <Logik> (1)
- Agrochemikalien (1)
- Bach (1)
- Boden (1)
- Bodenchemie (1)
- Bodenökologie (1)
- C++ (1)
- Calculus (1)
- Cations (1)
- Chironomus riparius (1)
- Computational Toxicology (1)
- Compute Shader (1)
- Computergraphik (1)
- Computervisualistik (1)
- Crayfish (1)
- Crayfish plague (1)
- Deduktion (1)
- Defi-Now! (1)
- Defibrillator (1)
- Differentia Scanning Calorimetry (1)
- Differential scanning calorimetry (1)
- E-KRHyper (1)
- E-KRHyper theorem prover (1)
- Edelkrebs (1)
- Emergenz (1)
- Endokrine Regulation (1)
- Englisch (1)
- Environmental Risk Assessment (1)
- Erste Hilfe (1)
- Fabric Simulation (1)
- First aid (1)
- Fledermäuse (1)
- Fluss (1)
- Fragebeantwortung (1)
- Gefrierpunktserniedrigung (1)
- Genetic diversity (1)
- Genetische Variabilität (1)
- Gewässer (1)
- Glasumwandlung (1)
- Glasübergang (1)
- Graphik (1)
- Hyaluronan (1)
- Hyaluronsäure (1)
- Hydratation (1)
- Hydration (1)
- Informatik (1)
- Integrated Model (1)
- Kation-Brücken (1)
- Kationen (1)
- Kognitive Linguistik (1)
- Konturfindung (1)
- Konzept (1)
- Krebspest (1)
- Landwirtschaft (1)
- Limology (1)
- Line Space (1)
- Linespace (1)
- Linked Data Modeling (1)
- Logischer Schluss (1)
- Magnetis (1)
- Methode (1)
- Mikroorganismus (1)
- Mixture Toxicity (1)
- N-Body Simulation (1)
- N-Körper Simulation (1)
- NMR-Spektroskopie (1)
- Non-freezing water (1)
- Nuclear Magnetic R (1)
- OWL (1)
- OpenGL (1)
- OpenGL Shading Language (1)
- Organische Bodensubstanz (1)
- Pestizid (1)
- Pestizide (1)
- Phylogeographie (1)
- Plasticization; Glass transition (1)
- Plastifizieren (1)
- Plastifizierung (1)
- Politik (1)
- Polysaccharide (1)
- Polysaccharides (1)
- Predictive Model (1)
- Programmierung (1)
- Prädikatenlogik (1)
- Präposition (1)
- RDF (1)
- Risikoabschätzung (1)
- Risikoanalyse (1)
- Risikomanagement (1)
- Schlussfolgern (1)
- Semantic Web (1)
- Simulation (1)
- Smartphone Applikation (1)
- Softwareergonomie (1)
- Steuerung (1)
- Stoffsimulation (1)
- Streams (1)
- Support System (1)
- Säugetiere (1)
- Süßwasserhaushalt (1)
- TBox (1)
- Text Analysis (1)
- Text Mining (1)
- Theorem prover (1)
- Theorembeweiser (1)
- Torf (1)
- Umweltchemikalie (1)
- Umwelttoxikologie (1)
- Umweltwissenschaften (1)
- Usability (1)
- Vocabulary Mapping (1)
- Wachstumsregler (1)
- Wirbellose (1)
- Wissensbasis (1)
- Zuckmücken (1)
- agent-based simulation (1)
- agriculture (1)
- aquatic ecotoxicology (1)
- automated theorem prover (1)
- bats (1)
- by-stander effect (1)
- cation bridges (1)
- cognitive linguistic approach (1)
- concept (1)
- ecological risk management (1)
- ecosystem functions (1)
- emergence (1)
- endocrine disrupting chemicals (1)
- endokrine Regulation (1)
- english prepositions (1)
- freshwater ecosystem (1)
- governance (1)
- invertebrates (1)
- knowledge base (1)
- landscape (1)
- life cycle test (1)
- mammals (1)
- microorganisms (1)
- minimum self-contained graphs (1)
- modelling (1)
- nicht gefrierbares Wasser (1)
- norm (1)
- peat (1)
- pesticide (1)
- pesticides (1)
- plant protection products (1)
- policy modelling (1)
- probabilistic (1)
- question answering (1)
- risk assessment (1)
- smartphone app (1)
- soil (1)
- soil organic matter (1)
- teaching (1)
- usability study (1)
- Ökosystem (1)
- Ökotoxologie (1)
Concept for a Knowledge Base on ICT for Governance and Policy Modelling regarding eGovPoliNet
(2013)
Abstract The EU project eGovPoliNet is engaged in research and development in the field of information and communication technologies (ICT) for governance and policy modelling. Numerous communities pursue similar goals in this field of IT-based, strategic decision making and simulation of social problem areas. Though, the existing research approaches and results so far are quite fragmented. The aim of eGovPoliNet is to overcome the fragmentation across disciplines and to establish an international, open dialogue by fostering the cooperation between research and practice. This dialogue will advance the discussion and development of various problem areas with the help of researchers from different disciplines, who share knowledge, expertise and best practice supporting policy analysis, modelling and governance. To support this dialogue, eGovPoliNet will provide a knowledge base, which's conceptual development is the subject of this thesis. The knowledge base is to be filled with content from the area of ICT for strategic decision making and social simulation, such as publications, ICT solutions and project descriptions. This content needs to be structured, organised and managed in a way, so that it generates added value and the knowledge base is used as source of accumulated knowledge, which consolidates the previously fragmented research and development results in a central location.
The aim of this thesis is the development of a concept for a knowledge base, which provides the structure and the necessary functionalities to gather and process knowledge concerning ICT solutions for governance and policy modelling. This knowledge needs to be made available to users and thereby motivate them to contribute to the development and maintenance of the knowledge base.
E-KRHyper is a versatile theorem prover and model generator for firstorder logic that natively supports equality. Inequality of constants, however, has to be given by explicitly adding facts. As the amount of these facts grows quadratically in the number of these distinct constants, the knowledge base is blown up. This makes it harder for a human reader to focus on the actual problem, and impairs the reasoning process. We extend E-Hyper- underlying E-KRhyper tableau calculus to avoid this blow-up by implementing a native handling for inequality of constants. This is done by introducing the unique name assumption for a subset of the constants (the so called distinct object identifiers). The obtained calculus is shown to be sound and complete and is implemented into the E-KRHyper system. Synthetic benchmarks, situated in the theory of arrays, are used to back up the benefits of the new calculus.
Tagging systems are intriguing dynamic systems, in which users collaboratively index resources with the so-called tags. In order to leverage the full potential of tagging systems, it is important to understand the relationship between the micro-level behavior of the individual users and the macro-level properties of the whole tagging system. In this thesis, we present the Epistemic Dynamic Model, which tries to bridge this gap between the micro-level behavior and the macro-level properties by developing a theory of tagging systems. The model is based on the assumption that the combined influence of the shared background knowledge of the users and the imitation of tag recommendations are sufficient for explaining the emergence of the tag frequency distribution and the vocabulary growth in tagging systems. Both macro-level properties of tagging systems are closely related to the emergence of the shared community vocabulary. rnrnWith the help of the Epistemic Dynamic Model, we show that the general shape of the tag frequency distribution and of the vocabulary growth have their origin in the shared background knowledge of the users. Tag recommendations can then be used for selectively influencing this general shape. In this thesis, we especially concentrate on studying the influence of recommending a set of popular tags. Recommending popular tags adds a feedback mechanism between the vocabularies of individual users that increases the inter-indexer consistency of the tag assignments. How does this influence the indexing quality in a tagging system? For this purpose, we investigate a methodology for measuring the inter-resource consistency of tag assignments. The inter-resource consistency is an indicator of the indexing quality, which positively correlates with the precision and recall of query results. It measures the degree to which the tag vectors of indexed resources reflect how the users perceive the similarity between resources. We argue with our model, and show it with a user experiment, that recommending popular tags decreases the inter-resource consistency in a tagging system. Furthermore, we show that recommending the user his/her previously used tags helps to increase the inter-resource consistency. Our measure of the inter-resource consistency complements existing measures for the evaluation and comparison of tag recommendation algorithms, moving the focus to evaluating their influence on the indexing quality.