Add to ORKGMining graph databases for frequent subgraphs has re-cently 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 “per-fect extension pruning ” in an earlier paper [2]. With it the number of generated fragments and visited search tree nodes can be reduced, thus accelerating the search. 1
A majority of the existing algorithms which mine graph datasets target complete, frequent sub-graph ...
Abstract. In the past few years many algprilluns for 4iscovering frequent subgraphs in graph databas...
Graphs are often used as models in very different application areas ranging from networks to molecul...
Summary. Mining graph databases for frequent subgraphs has recently developed into an area of intens...
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. Frequent approximate subgraph (FAS) mining has become an interesting task with wide applic...
In many recent applications, a graph is used to simulate many complex systems, such as social networ...
Abstract. The main practical problem encountered with frequent subgraph search methods is the tens o...
AbstractGiven a database of graphs, structure mining algorithms search for all substructures that sa...
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 ...
AbstractFrequent subgraph mining (FSM) is defined as finding all the subgraphs in a given graph that...
In this paper, we systematically explore the search space of frequent sequence mining and present tw...
A majority of the existing algorithms which mine graph datasets target complete, frequent sub-graph ...
Abstract. In the past few years many algprilluns for 4iscovering frequent subgraphs in graph databas...
Graphs are often used as models in very different application areas ranging from networks to molecul...
Summary. Mining graph databases for frequent subgraphs has recently developed into an area of intens...
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. Frequent approximate subgraph (FAS) mining has become an interesting task with wide applic...
In many recent applications, a graph is used to simulate many complex systems, such as social networ...
Abstract. The main practical problem encountered with frequent subgraph search methods is the tens o...
AbstractGiven a database of graphs, structure mining algorithms search for all substructures that sa...
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 ...
AbstractFrequent subgraph mining (FSM) is defined as finding all the subgraphs in a given graph that...
In this paper, we systematically explore the search space of frequent sequence mining and present tw...
A majority of the existing algorithms which mine graph datasets target complete, frequent sub-graph ...
Abstract. In the past few years many algprilluns for 4iscovering frequent subgraphs in graph databas...
Graphs are often used as models in very different application areas ranging from networks to molecul...