JCP
2008
13 years 4 months ago
2008
Existing frequent subgraph mining algorithms can operate efficiently on graphs that are sparse, have vertices with low and bounded degrees, and contain welllabeled vertices and edg...
IFIP12
2007
13 years 5 months ago
2007
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...
SIGMOD
2010
ACM
13 years 9 months ago
2010
ACM
Mining graph patterns in large networks is critical to a variety of applications such as malware detection and biological module discovery. However, frequent subgraphs are often i...
ICDM
2006
IEEE
13 years 10 months ago
2006
IEEE
Mining graph databases for frequent subgraphs has recently developed into an area of intensive research. Its main goals are to reduce the execution time of the existing basic algo...
ICDM
2007
IEEE
13 years 10 months ago
2007
IEEE
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...
ICDE
2006
IEEE
14 years 5 months ago
2006
IEEE
Most previously proposed frequent graph mining algorithms are intended to find the complete set of all frequent, closed subgraphs. However, in many cases only a subset of the freq...
ICDE
2006
IEEE
14 years 5 months ago
2006
IEEE
Existing graph mining algorithms typically assume that databases are relatively static and can fit into the main memory. Mining of subgraphs in a dynamic environment is currently ...