AbstractGraphs are common data structures used to represent / model real-world systems. Graph Mining is one of the arms of Data mining in which voluminous complex data are represented in the form of graphs and mining is done to infer knowledge from them. Frequent sub graph mining is a sub section of graph mining domain which is extensively used for graph classification, building indices and graph clustering purposes. The frequent sub graph mining is addressed from various perspectives and viewed in different directions based upon the domain expectations. In this paper, a survey is done on the approaches in targeting frequent sub graphs and various scalable techniques to find them
Graph data has been so prevalent that efficiently obtaining useful information from them is highly d...
In the current era of Big data, high volumes of valuable data can be generated at a high velocity fr...
In recent years there has been an increased interest in frequent pattern discovery in large database...
Data mining is a popular research area that has been studied by many researchers and focuses on find...
The Frequent Subgraph search plays a vital role to study structured graph with different level of im...
Abstract. The main practical problem encountered with frequent subgraph search methods is the tens o...
Large graphs are often used to simulate and model complex systems in variousresearch and application...
Due to rapid development of the Internet technology and new scientific advances, the number of appli...
This thesis describes research work undertaken in the field of graph-based knowledge discovery (or g...
AbstractFrequent subgraph mining (FSM) is defined as finding all the subgraphs in a given graph that...
Graphs are often used as models in very different application areas ranging from networks to molecul...
Over the years, frequent itemset discovery algorithms have been used to find interesting patterns in...
In many recent applications, a graph is used to simulate many complex systems, such as social networ...
Graphs are widely used in large scale social network analysis. Graph mining increasingly important i...
A majority of the existing algorithms which mine graph datasets target complete, frequent sub-graph ...
Graph data has been so prevalent that efficiently obtaining useful information from them is highly d...
In the current era of Big data, high volumes of valuable data can be generated at a high velocity fr...
In recent years there has been an increased interest in frequent pattern discovery in large database...
Data mining is a popular research area that has been studied by many researchers and focuses on find...
The Frequent Subgraph search plays a vital role to study structured graph with different level of im...
Abstract. The main practical problem encountered with frequent subgraph search methods is the tens o...
Large graphs are often used to simulate and model complex systems in variousresearch and application...
Due to rapid development of the Internet technology and new scientific advances, the number of appli...
This thesis describes research work undertaken in the field of graph-based knowledge discovery (or g...
AbstractFrequent subgraph mining (FSM) is defined as finding all the subgraphs in a given graph that...
Graphs are often used as models in very different application areas ranging from networks to molecul...
Over the years, frequent itemset discovery algorithms have been used to find interesting patterns in...
In many recent applications, a graph is used to simulate many complex systems, such as social networ...
Graphs are widely used in large scale social network analysis. Graph mining increasingly important i...
A majority of the existing algorithms which mine graph datasets target complete, frequent sub-graph ...
Graph data has been so prevalent that efficiently obtaining useful information from them is highly d...
In the current era of Big data, high volumes of valuable data can be generated at a high velocity fr...
In recent years there has been an increased interest in frequent pattern discovery in large database...