2012, Nagel, Uwe, Thiel, Kilian, Kötter, Tobias, Piatek, Dawid, Berthold, Michael R.

The discovery of surprising relations in large, heterogeneous information repositories is gaining increasing importance in real world data analysis. If these repositories come from diverse origins, forming different domains, domain bridging associations between otherwise weakly connected domains can provide insights into the data that are not accomplished by aggregative approaches. In this paper, we propose a first formalization for the detection of such potentially interesting, domaincrossing relations based purely on structural properties of a relational knowledge description.

2011, Nagel, Uwe, Thiel, Kilian, Kötter, Tobias, Piatek, Dawid, Berthold, Michael R.

The discovery of surprising relations in large, heterogeneous information repositories is gaining increasing importance in real world data analysis. If these repositories come from diverse origins, forming different domains, domain bridging associations between otherwise weakly connected domains can provide insights into the data that can otherwise not be accomplished. In this paper, we propose a first formalization for the detection of such potentially interesting, domain-crossing relations based purely on structural properties of a relational knowledge description.

2009, Berthold, Michael R., Brandes, Ulrik, Kötter, Tobias, Mader, Martin, Nagel, Uwe, Thiel, Kilian

Almost every application of spreading activation is accompanied by its own set of often heuristic restrictions on the dynamics. We show that in constraint-free scenarios spreading activation would actually yield query-independent results, so that the specific choice of restrictions is not only a pragmatic computational issue, but crucially determines the outcome.