Linked Data on the Web is either created from structured data sources (such as relational databases), from semi-structured sources (such as Wikipedia), or from unstructured sources (such as text). In the latter two cases, the generated Linked Data will likely be noisy and incomplete. In this paper, we present two algorithms that exploit statistical distributions of properties and types for enha...

Knowledge ‘decay’ is a measure of the degradation of knowledge integrity. In a unified knowledge representation, data, information and knowledge are all represented in a single formalism as “items”. A unified knowledge representation is extended here to include two measures of knowledge integrity. A rule of inference is defined on the unified knowledge representation that preserves the validity...

As the real world evolves, the information contained in the knowledge bases is updated accordingly and the evolution history of entities and their properties becomes of great interest to users, who thus need effective query tools to explore it. In this paper, we (i) introduce SPARQL and its user-friendly interface for expressing powerful structured queries on the history of RDF knowledge bases,...

Recent trends in information extraction have allowed us to not only extract large semantic knowledge bases from structured or loosely structured Web sources, but to also extract additional annotations along with the RDF facts these knowledge bases contain. Among the most important types of annotations are spatial and temporal annotations. In particular the latter temporal annotations help us to...

The paper proposes that the basic idea of the WWW can be generalized to the domain of data structures or information structures. This means that \packages" of structured information are represented as short text les, stored in web-accessible locations (URL:s), and are loaded as needed by the web-oriented database tool. We suggest that this technique may help to get done what has not been achiev...

We develop a new methodology and tool for knowledge acquisition under uncertainty. A new knowledge representation called Bayesian Knowledge Bases provides a powerful key to our approach and is well-grounded in probability theory. In this paper, we demonstrate the ease and flexibility with which knowledge acquisition can be accomplished while ensuring the consistency of the knowledge base as dat...