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- Zhaonian Zou, Hong Gao, Jianzhong Li
- KDD
- 2010

Frequent subgraph mining has been extensively studied on certain graph data. However, uncertainties are inherently accompanied with graph data in practice, and there is very few work on mining uncertain graph data. This paper investigates frequent subgraph mining on uncertain graphs under probabilistic semantics. Specifically, a measure called… (More)

- Shuo Zhang, Jianzhong Li, Hong Gao, Zhaonian Zou
- EDBT
- 2009

In recent years, large amount of data modeled by graphs, namely graph data, have been collected in various domains. Efficiently processing queries on graph databases has attracted a lot of research attentions. <i>Supergraph query</i> is a kind of new and important queries in practice. A <i>supergraph query, q</i>, on a graph database <i>D</i> is to retrieve… (More)

- Zhaonian Zou, Jianzhong Li, Hong Gao, Shuo Zhang
- IEEE Transactions on Knowledge and Data…
- 2010

In many real applications, graph data is subject to uncertainties due to incompleteness and imprecision of data. Mining such uncertain graph data is semantically different from and computationally more challenging than mining conventional exact graph data. This paper investigates the problem of mining uncertain graph data and especially focuses on mining… (More)

- Zhaonian Zou, Jianzhong Li, Hong Gao, Shuo Zhang
- CIKM
- 2009

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 computationally more challenging than mining exact graph data. This paper investigates the problem of mining frequent subgraph patterns from uncertain graph data. The frequent subgraph… (More)

- Zhaonian Zou, Jianzhong Li, Hong Gao, Shuo Zhang
- 2010 IEEE 26th International Conference on Data…
- 2010

Existing studies on graph mining focus on exact graphs that are precise and complete. However, graph data tends to be uncertain in practice due to noise, incompleteness and inaccuracy. This paper investigates the problem of finding top-k maximal cliques in an uncertain graph. A new model of uncertain graphs is presented, and an intuitive measure is… (More)

- Jianzhong Li, Zhaonian Zou, Hong Gao
- The VLDB Journal
- 2012

Frequent subgraph mining has been extensively studied on certain graph data. However, uncertainty is intrinsic in graph data in practice, but there is very few work on mining uncertain graph data. This paper focuses on mining frequent subgraphs over uncertain graph data under the probabilistic semantics. Specifically, a measure called $${\varphi}$$… (More)

- Zhaonian Zou
- 2013

This paper studies the problem of finding the densest subgraph in an uncertain graph. Due to uncertainty in graphs, the traditional definitions of dense subgraphs are not applicable to uncertain graphs. In this paper, we introduce the expected density of an uncertain graph. Based on the expected density, we formalize the problem that, given an uncertain… (More)

- Zhaonian Zou, Rong Zhu
- Knowledge and Information Systems
- 2016

The k-truss of a graph is the largest edge-induced subgraph such that every edge is contained in at least k triangles within the subgraph, where a triangle is a cycle consisting of three vertices. As a new notion of cohesive subgraphs, truss has recently attracted a lot of research attentions in the database and data mining fields. At the same time,… (More)

- Zhaonian Zou, Jianzhong Li
- 2013 IEEE 13th International Conference on Data…
- 2013

Structural-context similarities between vertices in graphs, such as the Jaccard similarity, the Dice similarity, and the cosine similarity, play important roles in a number of graph data analysis techniques. However, uncertainty is inherent in massive graph data, and therefore the classical definitions of structural-context similarities on exact graphs… (More)