Motivating contributors is an important task for owners of online communities. Literature provides multiple suggestions to motivate users to increase content contribution.
Nowadays, large collections of photos are tagged with GPS coordinates. The modelling of such large geo-tagged corpora is an important problem in data mining and information retrieval, and involves the use of geographical information to detect topics with a spatial component.
In the same way that we publish a corporate Website to describe who we are and the work we carry out, it is important to publish RDF descriptions about WeST on the Web of Data.
The Live+Gov project is concerned with detecting attributes of the environment of urban citizens by exploiting sensor data from mobile phones. One aspect of this problem is the recognition of human activities, like "walking", "running" or "standing". This information is used used, a.o. for analyzing public transportation systems ("How long you wait for the bus?").
In this talk, I will discuss the frontiers and the fruitful connections between the semantic web and argumentation theory. In particular, I will describe two approaches exploiting the connections of semantic web and argumentation techniques to address open issues in the web scenario.
One of the major challenges for the next years in computer science is how we can handle massive amounts of semantic data in an elegant and efficient way.
Approaches for multi-agent systems range from frameworks dedicated to specific problem domains to very flexible systems similar to text-based or graphical programming languages.
We propose Semantic Relevance Distance (SRD): a novel metric for computing semantic relatedness between terms. SRD makes use of a controlled reference corpus for a statistical analysis of the relatedness of terms.
At the end of 2013 I want to draw a conclusion about this year, stating where we are and where we are going.
Metadata, describing the content of photos, are of high importance for applications like image search or as part of training sets for object detection algorithms. In this work, we apply tags to image regions for a more detailed description of the photo semantics.