The problem of discovering frequent subgraphs of graph data can be solved by constructing a candidate set of subgraphs first, and then, identifying within this candidate set those...
This paper introduces a new technique of document clustering based on frequent senses. The proposed system, GDClust (Graph-Based Document Clustering) works with frequent senses ra...
Attributed graphs are increasingly more common in many application domains such as chemistry, biology and text processing. A central issue in graph mining is how to collect inform...
Mining frequent subgraphs is an area of research where we have a given set of graphs, and where we search for (connected) subgraphs contained in many of these graphs. Each graph ca...
Edgar H. de Graaf, Joost N. Kok, Walter A. Kosters
In systems of interacting entities such as social networks, interactions that occur regularly typically correspond to significant, yet often infrequent and hard to detect, interact...