An important area of data mining is anomaly detection, particularly for fraud. However, little work has been done in terms of detecting anomalies in data that is represented as a g...
The integration of heterogenous data sources is a crucial step for the upcoming semantic web – if existing information is not integrated, where will the data come from that the s...
A universal data model, named DG, is introduced to handle vectorized data uniformly during the whole recognition process. The model supports low level graph algorithms as well as h...
This paper gives a theoretical framework for clustering a set of conceptual graphs characterized by sparse descriptions. The formed clusters are named in an intelligible manner thr...
Abstract Polynomial-time data reduction is a classical approach to hard graph problems. Typically, particular small subgraphs are replaced by smaller gadgets. We generalize this ap...