Explanation Retrieval in Semantic Networks : Understanding Spreading Activation based Recommendations

Spreading Activation is a well-known semantic search technique to determine the relevance of nodes in a semantic network. When used for decision support, meaningful explanations of semantic search results are crucial for the user’s acceptance and trust. Usually, explanations are generated based on the original network. Indeed, the data accumulated during the spreading activation process contains semantically extremely valuable information. Therefore, our approach exploits the so-called spread graph, a specific data structure that comprises the spreading progress data. In this paper, we present a three-step explanation retrieval method based on spread graphs. We show how to retrieve the most relevant parts of a network by minimization and extraction techniques and formulate meaningful explanations. The evaluation of the approach is then performed with a prototypical decision support system for automotive safety analyses

Removal of redundant elements within UML activity diagrams

As the complexity of systems continues to rise, the use of model-driven development approaches becomes more widely applied. Still, many created models are mainly used for documentation. As such, they are not designed to be used in following stages of development, but merely as a means of improved overview and communication. In an effort to use existing UML2 activity diagrams of an industry partner (Daimler AG) as a source for automatic generation of software artifacts, we discovered, that the diagrams often contain multiple instances of the same element. These redundant instances might improve the readability of a diagram. However, they complicate further approaches such as automated model analysis or traceability to other artifacts because mostly redundant instances must be handled as one distinctive element. In this paper, we present an approach to automatically remove redundant ExecutableNodes within activity diagrams as they are used by our industry partner. The removal is implemented by merging the redundant instances to a single element and adding additional elements to maintain the original behavior of the activity. We use reachability graphs to argue that our approach preserves the behavior of the activity. Additionally, we applied the approach to a real system described by 36 activity diagrams. As a result 25 redundant instances were removed from 15 affected diagrams