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The modeling of concepts from a cognitive perspective is important for designing spatial information systems that interoperate with human users. Concept representations that are built using geometric and topological conceptual space structures are well suited for semantic similarity and concept combination operations. In addition, concepts that are more(More)
One of the key deficiencies of the Semantic Web is its lack of cognitive plausibility. We argue that by accounting for people's reasoning mechanisms and cognitive representations, the usefulness of information coming from the Semantic Web will be enhanced. More specifically, the utilization and integration of conceptual spaces is proposed as a knowledge(More)
CSML is a semantic markup language created for the publishing and sharing of conceptual spaces, which are geometric structures that represent semantics at the conceptual level. CSML can be used to describe semantics that are not captured well by the ontology languages commonly used in the Semantic Web. Measurement of the semantic similarity of concepts as(More)
Computing user similarity is key for personalized location-based recommender systems and geographic information retrieval. So far, most existing work has focused on structured or semi-structured data to establish such measures. In this work, we propose topic mod-eling to exploit sparse, unstructured data, e.g., tips and reviews, as an additional feature to(More)
To a large degree, the attraction of Big Data lies in the variety of its heterogeneous multi-thematic and multi-dimensional data sources and not merely its volume. To fully exploit this variety, however, requires conflation. This is a two step process. First, one has to establish identity relations between information entities across the different data(More)
The semantic integration of heterogeneous, spatiotemporal information is a major challenge for achieving the vision of a multi-thematic and multi-perspective Digital Earth. The Semantic Web technology stack has been proposed to address the integration problem by knowledge representation languages and reasoning. However approaches such as the Web Ontology(More)
Semantic similarity measurement is a key methodology in various domains ranging from cognitive science to geographic information retrieval on the Web. Meaningful notions of similarity, however, cannot be determined without taking additional contextual information into account. One way to make similarity measures context-aware is by introducing weights for(More)
When experiencing or describing a new place people will often compare it against other places that they already know. However, this human attention to the simultaneous similarities and differences between places is not reflected in the design of user interfaces of current place search technologies. In this demo, we present Frankenplace, an application for(More)