NDLI: Fast best-effort pattern matching in large attributed graphs

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Fast best-effort pattern matching in large attributed graphs

Content Provider	ACM Digital Library
Author	Tong, Hanghang Eliassi-Rad, Tina Gallagher, Brian Faloutsos, Christos
Abstract	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. This is the first main feature of our method. It 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 don't exist. Its second feature is scalability. In general, if the query has $n_{q}$ nodes and the data graph has n nodes, the problem needs polynomial time complexity O(n $^{n}$ $^{q}),$ which is prohibitive. Our G-Ray ("Graph X-Ray") method finds high-quality subgraphs in time linear on the size of the data graph. Experimental results on the DLBP author-publication graph (with 356K nodes and 1.9M edges) illustrate both the effectiveness and scalability of our approach. The results agree with our intuition, and the speed is excellent. It takes 4 seconds on average fora 4-node query on the DBLP graph.
Starting Page	737
Ending Page	746
Page Count	10
File Format	PDF
ISBN	9781595936097
DOI	10.1145/1281192.1281271
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2007-08-12
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Pattern match Random walk Attributed graph
Content Type	Text
Resource Type	Article

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