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.
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.
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.
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.
The exploration and integration of linked data into programming environments has to deal with two different data represen- tation principles.
Data on the Linked Open Data (LOD) cloud changes frequently. Recent approaches focus on quantifying the changes in the LOD cloud. These metrics are capable to determine changes between two different versions of a dataset, but do not measure the dynamics.
The Web, traditionally viewed as a vast repository of documents, is being transformed into a huge database by the massive presence of structured data. There are several efforts to publish, describe, organise and interlink structured data on the Web.