Wikidata is a free, collaborative knowledge base created and boosted by Wikimedia Deutschland, and developed by a large community of volunteers all over the world. After almost 4 years, Wikidata has a community of 16 thousand active editors that has managed to create a knowledge graph with 20+ million notorious entities.
Inconsistent information in logical specifications is a ubiquitous phenomenon in many areas such as knowledge representation, software requirements engineering, database management, and semantic web. In order to analyze inconsistency and provide hints to repair it, inconsistency measures have been developed that can quantitatively assess the severity of inconsistency.
This presentation deals with the question of how linked data can be used to improve the search for information in a business enterprise. The aimed goal was the development of a concept for a knowledge graph to improve the company's internal data structure as well as the search for information within the company. The aimed goal was the development of a concept for a knowledge graph to improve the company's internal data structure as well as the search for information within the company.
Das Koldfish Projekt der Universität Koblenz hat sich als Ziel gesetzt Endbenutzer bei der Entwicklung von Applikationen gegen das Semantic Web zu unterstützen, indem es als Middleware zwischen Semantic Web und Applikation wiederkehrende Herausforderungen, wie etwa die Akquise und Verwaltung von (freien) verknüpften Daten, übernimmt. Die Kernfunktionalität ist dabei die Suche und Speicherung dieser in Form von RDF Graphen vorliegenden Linked (open) Data.
The Koldfish project is our institute's effort to improve usability of Linked Open Data. In this talk, we provide in which parts we help developers and data users. We also want to initiate a fruitful discussion on how other methods and tools of our institute could be integraded to the project as well as the development of new ideas.
We provide new insights into the area of combining abstract argumentation frameworks with probabilistic reasoning. In particular, we consider the scenario when assessments on the probabilities of a subset of the arguments is given and the probabilities of the remaining arguments have to be derived, taking both the topology of the argumentation framework and principles of probabilistic reasoning into account.
Its one of the most popular YouTube videos ever produced, having been viewed more than 840 million times. Its hard to understand why this clip is so famous and actually went viral, since nothing much happens. Two little boys, Charlie and Harry, are sitting in a chair when Charlie, the younger brother, mischievously bites Harrys finger. Theres a shriek and then a laugh. The clip is called “Charlie Bit My Finger–Again!”
We study the attention dynamics towards prominent scientists by analyzing different Web signals. In our research we demonstrate how success of the scientist is related to the success of the scientific field he is working in. We use unsupervised learning techniques to discover the attention patterns in the time series. Based on these patterns we try to predict the future success of the scientist.
We investigate the relationship between semantics for formal argumentation and measures from social networking theory. In particular, we consider using matrix exponentials, which are measures used for link prediction and recommendation in social networks, as a way to measure acceptability of arguments in abstract argumentation frameworks.
Word embeddings are mappings of words to dense, real-valued vectors. The word embeddings that were created as a by-product of training neural networks for the task of language modelling were shown to encoded certain syntactic and semantic regularities. This talk will give a quick introduction to neural networks, will explain how they can be applied to the task of language modelling, and will discuss semantic properties of word embeddings. Lastly, the goal of Lukas' thesis will be presented.