Summary. 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 algorithms and to enhance their capability to find meaning-ful graph fragments. Here we present a method to achieve the former, namely an improvement of what we called “perfect extension pruning ” in an earlier paper [4]. With this method the number of generated fragments and visited search tree nodes can be reduced, often considerably, thus accelerating the search. We describe the method in detail and present experimental results that demonstrate its usefulness.
A majority of the existing algorithms which mine graph datasets target complete, frequent sub-graph ...
ABSTRACT: In recent years, graph mining has attracted much attention in the data mining community. S...
AbstractGiven a database of graphs, structure mining algorithms search for all substructures that sa...
Mining graph databases for frequent subgraphs has re-cently developed into an area of intensive rese...
Mining graph databases for frequent subgraphs has recently developed into an area of intensive resea...
In recent years several algorithms for mining frequent subgraphs in graph databases have been propos...
The exponential number of possible subgraphs makes the problem of frequent subgraph mining a challen...
Abstract. The main practical problem encountered with frequent subgraph search methods is the tens o...
In many recent applications, a graph is used to simulate many complex systems, such as social networ...
Abstract. In the past few years many algprilluns for 4iscovering frequent subgraphs in graph databas...
Abstract. Frequent approximate subgraph (FAS) mining has become an interesting task with wide applic...
A majority of the existing algorithms which mine graph datasets target complete, frequent sub-graph ...
To our best knowledge, all existing graph pattern mining al-gorithms can only mine either closed, ma...
A majority of the existing algorithms which mine graph datasets target complete, frequent sub-graph ...
Graphs are often used as models in very different application areas ranging from networks to molecul...
A majority of the existing algorithms which mine graph datasets target complete, frequent sub-graph ...
ABSTRACT: In recent years, graph mining has attracted much attention in the data mining community. S...
AbstractGiven a database of graphs, structure mining algorithms search for all substructures that sa...
Mining graph databases for frequent subgraphs has re-cently developed into an area of intensive rese...
Mining graph databases for frequent subgraphs has recently developed into an area of intensive resea...
In recent years several algorithms for mining frequent subgraphs in graph databases have been propos...
The exponential number of possible subgraphs makes the problem of frequent subgraph mining a challen...
Abstract. The main practical problem encountered with frequent subgraph search methods is the tens o...
In many recent applications, a graph is used to simulate many complex systems, such as social networ...
Abstract. In the past few years many algprilluns for 4iscovering frequent subgraphs in graph databas...
Abstract. Frequent approximate subgraph (FAS) mining has become an interesting task with wide applic...
A majority of the existing algorithms which mine graph datasets target complete, frequent sub-graph ...
To our best knowledge, all existing graph pattern mining al-gorithms can only mine either closed, ma...
A majority of the existing algorithms which mine graph datasets target complete, frequent sub-graph ...
Graphs are often used as models in very different application areas ranging from networks to molecul...
A majority of the existing algorithms which mine graph datasets target complete, frequent sub-graph ...
ABSTRACT: In recent years, graph mining has attracted much attention in the data mining community. S...
AbstractGiven a database of graphs, structure mining algorithms search for all substructures that sa...