Motivation: For many years now, research in intelligent spaces has grown, exploring different ways that a room can react to one or more users and their actions. As usage of this type of environment grows, however, these spaces will by necessity collect ever-increasing amounts of data about their users, in order to adapt to the user’s desires. Information will be collected on the users’ interest...

According to Dynamic Logic Programming (DLP), knowledge may be given by a sequence of theories (encoded as logic programs) representing different states of knowledge. These may represent time (e.g. in updates), specificity (e.g. in taxonomies), strength of updating instance (e.g. in the legislative domain), hierarchical position of knowledge source (e.g. in organizations), etc. The mutual relat...

Current expert systems represent knowledge in several different forms. In most cases, there is an object or inheritance hierarchy representing static facts about the objects, actions, or events in the domain of application, and the important relationships between them. Other types of knowledge are represented in the form of rules, usually conditionals saying what action should be performed if s...

Entity images provide significant visual information that helps the construction of knowledge representations. Most conventional methods learn knowledge representations solely from structured triples, ignoring rich visual information extracted from entity images. In this paper, we propose a novel Image-embodied Knowledge Representation Learning model, where knowledge representations are learned...

Inter-word associations like stagger drunken, or intra-word sense divisions (e.g. write a diary vs. write an article) are difficult to compile using a traditional lexicographic approach. As an alternative, we present a model that reflects this kind of subtle lexical knowledge. Based on the minimal sense of a word (clique), the model (1) selects contextually related words (contexonyms) and (2) c...

Frame knowledge representation systems lack two important capabilities that prevent them from scaling up to large applications: they do not support fast access to large knowledge bases (KBs), nor do they provide concurrent multiuser access to shared KBs. We describe the design and implementation of a storage subsystem that submerges a database management system (DBMS) within a knowledge represe...

The theory of probability is widely used in biomedical research for data analysis and modelling. In previous work the probabilities of the research hypotheses have been recorded as experimental metadata. The ontology HELO is designed to support probabilistic reasoning, and provides semantic descriptors for reporting on research that involves operations with probabilities. HELO explicitly links ...

Exploiting the full potential of the World Wide Web will require semantic as well as syntactic interoperability. This can best be achieved by providing a further representation and inference layer that builds on existing and proposed web standards. The OIL language extends the RDF schema standard to provide just such a layer. It combines the most attractive features of frame based languages wit...