Mining discriminative features for graph data has attracted much attention in recent years due to its important role in constructing graph classifiers, generating graph indices, etc. Most measurement of interestingness of discriminative subgraph features are defined on certain graphs, where the structure of graph objects are certain, and the binary edges within each graph represent the "presenc...

this paper deals with leader-following and leaderless consensus problems of high-order multi-input/multi-output (mimo) multi-agent systems with unknown nonlinear dynamics in the presence of uncertain external disturbances. the agents may have different dynamics and communicate together under a directed graph. a distributed adaptive method is designed for both cases. the structures of the contro...

The quadratic minimum spanning tree problem is to find a spanning tree on a graph that minimizes a quadratic objective function of the edge weights. In this paper, the quadratic minimum spanning tree problem is concerned on the graph with edge weights being assumed as uncertain variables. The notion of the uncertain quadratic -minimum spanning tree is introduced by using the uncertain chance co...

A dynamic uncertain causality graph (DUCG) is a probabilistic graphical model for knowledge representation and reasoning, which has been widely used in many areas, such as safety assessment, medical diagnosis, fault diagnosis. However, the convention DUCG fails to experts’ precisely because parameters were crisp numbers or fuzzy numbers. In reality, domain experts tend use linguistic terms expr...

Graph has become a widely used structure to model data. Unfortunately, data are inherently with uncertainty because of the occurrence of noise and incompleteness in data collection. This is why uncertain graphs catch much attention of researchers. However, the uncertain graph models in existing works assume all edges in a graph are independent of each other, which dose not really make sense in ...

Capturing the branching flow of events described in text aids a host of tasks, from summarization to narrative generation to classification and prediction of events at points along the flow. In this paper, we present a framework for the automatic generation of an uncertain, temporally directed event graph from online sources such as news stories or social media posts. The vertices are generated...

This paper studies the top-k possible shortest path (kSP) queries in a large uncertain graph, specifically, given two vertices S and T , a kSP query reports the top-k possible shortest paths from S to T . Different from existing solutions for uncertain graph problems, we adopt the possible worlds semantics. Although possible worlds semantics have been studied widely in relational databases, the...

A large number of applications such as querying sensor networks, and analyzing proteinprotein interaction (PPI) networks, rely on mining uncertain graph and hypergraph databases. In this work we study the following problem: Given an uncertain, weighted (hyper)graph, how can we efficiently find a (hyper)matching with high expected reward, and low risk? This problem naturally arises in the contex...