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With the increasing popularity of Web 2.0 streams, people become overwhelmed by the available information. This is partly countered by tagging blog posts and tweets, so that users can filter messages according to their tags. However, this is insufficient for detecting newly emerging topics that are not reflected by a single tag but are rather expressed by(More)
Emergent topics are newly arising themes in news, blogs, or tweets, often implied by interesting and unexpected correlations of tags or entities. We present the enBlogue system for emergent topic detection. The name enBlogue reflects the analogy with emerging trends in fashion often referred to as en Vogue. EnBlogue continuously monitors Web 2.0 streams and(More)
Everything is relative. Cars are compared by gas per mile, websites by page rank, students based on GPA, scientists by number of publications, and celebrities by beauty or wealth. In this paper, we study the characteristics of such entity rankings based on a set of rankings obtained from a popular Web portal. The obtained insights are integrated in our(More)
Halls of Fame are fascinating constructs. They represent the elite of an often very large amount of entities—persons, companies, products, countries etc. Beyond their practical use as static rankings, changes to them are particularly interesting—for decision making processes, as input to common media or novel narrative science applications, or simply(More)
In this work we consider the continuous computation of set correlations over a stream of set-valued attributes, such as Tweets and their hashtags, social annotations of blog posts obtained through RSS, or updates to set-valued attributes of databases. In order to compute tag correlations in a distributed fashion, all necessary information has to be present(More)
Earth observation sciences, astronomy, and seismology have large data sets which have inherently rich spatial and geospa-tial information. In combination with large collections of semantically rich objects which have a large number of thematic properties, they form a new source of knowledge for urban planning, smart cities and natural resource management.(More)
The popularity, availability and sizes of point cloud data sets are increasing, thus raising interesting data management and processing challenges. Various software solutions are available for the management of point cloud data. A benchmark for point cloud data management systems was defined and it was executed for several solutions. In this paper we focus(More)
LIDAR is a popular remote sensing method used to examine the surface of the Earth. LIDAR instruments use light in the form of a pulsed laser to measure ranges (variable distances) and generate vast amounts of precise three dimensional point data describing the shape of the Earth. Processing large collections of point cloud data and combining them with(More)