Graph has become increasingly important in modelling complicated structures and schemaless data such as proteins, chemical compounds, and XML documents. Given a graph query, it is...
Graph data are subject to uncertainties in many applications due to incompleteness and imprecision of data. Mining uncertain graph data is semantically different from and computat...
In this paper we study the problem of mining all frequent queries in a given database table, a problem known to be intractable even for conjunctive queries. We restrict our attent...
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...
Frequent pattern mining has been studied extensively. However, the effectiveness and efficiency of this mining is often limited, since the number of frequent patterns generated i...