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KDD
2007
ACM

Fast best-effort pattern matching in large attributed graphs

10 years 11 months ago
Fast best-effort pattern matching in large attributed graphs
We focus on large graphs where nodes have attributes, such as a social network where the nodes are labelled with each person's job title. In such a setting, we want to find subgraphs that match a user query pattern. For example, a `star' query would be, "find a CEO who has strong interactions with a Manager, a Lawyer, and an Accountant, or another structure as close to that as possible". Similarly, a `loop' query could help spot a money laundering ring. Traditional SQL-based methods, as well as more recent graph indexing methods, will return no answer when an exact match does not exist. Our method can find exact-, as well as near-matches, and it will present them to the user in our proposed `goodness' order. For example, our method tolerates indirect paths between, say, the `CEO' and the `Accountant' of the above sample query, when direct paths do not exist. Its second feature is scalability. In general, if the query has nq nodes and the data gr...
Hanghang Tong, Christos Faloutsos, Brian Gallagher
Added 30 Nov 2009
Updated 30 Nov 2009
Type Conference
Year 2007
Where KDD
Authors Hanghang Tong, Christos Faloutsos, Brian Gallagher, Tina Eliassi-Rad
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