Uncertain data are data with uncertainty information, which exist widely in database
applications. In recent years, uncertainty in data has brought challenges in almost all …

Graphs play an important role in modern world, due to their widespread use for modeling,
representing and organizing linked data. Taking into consideration that most of the “killer” …

We study the problem of clustering probabilistic graphs. Similar to the problem of clustering
standard graphs, probabilistic graph clustering has numerous applications, such as finding …

As uncertainty is inherent in a wide spectrum of graph applications such as social network
and brain network, it is highly demanded to re-visit classical graph problems in the context of …

A hypergraph is a complex data structure capable of expressing associations among any
number of data entities. Overcoming the limitations of traditional graphs, hypergraphs are …

Many graphs in practical applications are not deterministic, but are probabilistic in nature
because the existence of the edges is inferred with the use of a variety of statistical …

Uncertainty is intrinsic to a wide spectrum of real-life applications, which inevitably applies to
graph data. Representative uncertain graphs are seen in bio-informatics, social networks …

As a popular search mechanism, keyword search has been applied to retrieve useful data in
documents, texts, graphs, and even relational databases. However, so far, there is no work …

Frequent subgraph mining (FSM) plays an important role in graph mining, attracting a great
deal of attention in many areas, such as bioinformatics, web data mining and social …

Extracting frequent patterns from databases has always been an imperative task for the data
mining community. Literature has endowed plentiful endeavors to this research area with …