Quite often, Linked Open Data (LOD) applications pre-fetch data from the Web and store local copies of it in a cache for faster access at runtime. Yet, recent investigations have shown that data published and interlinked on the LOD cloud is subject to frequent changes.
In anticipation of RDF graphs exceeding one trillion triples, the W3C tested RDF stores whether they can deal with such huge graphs. This amount of data can be stored in a cloud at a reasonable price. But storing a graph in a cloud consisting of several individual computers raises several issues like the triple placement or the efficient processing of interactive queries.
In this talk I will review and evaluate models of network evolution based on the notion of structural diversity. I show that diversity is an underlying theme of three principles of network evolution: the preferential attachment model, connectivity and link prediction. I show that in all three cases, a dominant trend towards shrinking diversity is apparent, both theoretically and empirically.
Identifying suitable data sets is a crucial task in several fields of application, like data analysis, but the task itself is highly complicated and mostly heavily related to manually skimming through a vast amounts of data.
An claim made quite often is that types in RDF and the Semantic Web differ fundamentally from the types as they exist in programming languages. The claim is usually aimed towards the way modern, existing languages treat data types.
Wikidata, the free knowledge base of Wikipedia, is one of the largest collections of human-authored structured information that are freely available on the Web. It is curated by a unique community of tens of thousands of editors who contribute in up to 400 different languages.
A common use case within SAP business applications is the retrieval of electronic documents from external archives via a HTTP based protocol called ArchiveLink. Typically, these documents are each being accompanied by a large set of contextual, application specific business data.
Die Service Line Detection (SLD) behandelt die Erkennung von Verbindungslinien öffentlicher Verkehrsmittel wie Bussen, Zügen oder Straßenbahnen, mit denen sich eine Person fortbewegt. Bisherige Untersuchungen konzentrierten sich vor allem auf die Strecke, die z.B. ein Bus entlang fährt.
Successful and robust grasping for humanoid robots is still an ongoing research topic in robotics. Applying human-inspired grasping strategies does not only correspond with more natural looking motions but can also yield good results regarding task success when having to deal with uncertainty.
The Linked Data cloud has seen a tremendous and continuing growth over the last couple of years. In order to consume Linked Data, many scenarios require complex and computationally intensive operations on focused subsets of the Linked Open Data (LOD) cloud.