### Abstract

Graph pattern matching is typically defined in terms of subgraph isomorphism, which makes it an np-complete problem. Moreover, it requires bijective functions, which are often too restrictive to characterize patterns in emerging applications. We propose a class of graph patterns, in which an edge denotes the connectivity in a data graph within a predefined number of hops. In addition, we define matching based on a notion of bounded simulation, an extension of graph simulation. We show that with this revision, graph pattern matching can be performed in cubic-time, by providing such an algorithm. We also develop algorithms for incrementally finding matches when data graphs are updated, with performance guarantees for dag patterns. We experimentally verify that these algorithms scale well, and that the revised notion of graph pattern matching allows us to identify communities commonly found in real-world networks.

Original language | English |
---|---|

Title of host publication | Proceedings of the VLDB Endowment |

Pages | 264-275 |

Number of pages | 12 |

Volume | 3 |

Edition | 1 |

Publication status | Published - Sep 2010 |

Externally published | Yes |

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### ASJC Scopus subject areas

- Computer Science (miscellaneous)
- Computer Science(all)

### Cite this

*Proceedings of the VLDB Endowment*(1 ed., Vol. 3, pp. 264-275)

**Graph pattern matching : From intractable to polynomial time.** / Fan, Wenfei; Li, Jianzhong; Ma, Shuai; Tang, Nan; Wu, Yinghui; Wu, Yunpeng.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

*Proceedings of the VLDB Endowment.*1 edn, vol. 3, pp. 264-275.

}

TY - CHAP

T1 - Graph pattern matching

T2 - From intractable to polynomial time

AU - Fan, Wenfei

AU - Li, Jianzhong

AU - Ma, Shuai

AU - Tang, Nan

AU - Wu, Yinghui

AU - Wu, Yunpeng

PY - 2010/9

Y1 - 2010/9

N2 - Graph pattern matching is typically defined in terms of subgraph isomorphism, which makes it an np-complete problem. Moreover, it requires bijective functions, which are often too restrictive to characterize patterns in emerging applications. We propose a class of graph patterns, in which an edge denotes the connectivity in a data graph within a predefined number of hops. In addition, we define matching based on a notion of bounded simulation, an extension of graph simulation. We show that with this revision, graph pattern matching can be performed in cubic-time, by providing such an algorithm. We also develop algorithms for incrementally finding matches when data graphs are updated, with performance guarantees for dag patterns. We experimentally verify that these algorithms scale well, and that the revised notion of graph pattern matching allows us to identify communities commonly found in real-world networks.

AB - Graph pattern matching is typically defined in terms of subgraph isomorphism, which makes it an np-complete problem. Moreover, it requires bijective functions, which are often too restrictive to characterize patterns in emerging applications. We propose a class of graph patterns, in which an edge denotes the connectivity in a data graph within a predefined number of hops. In addition, we define matching based on a notion of bounded simulation, an extension of graph simulation. We show that with this revision, graph pattern matching can be performed in cubic-time, by providing such an algorithm. We also develop algorithms for incrementally finding matches when data graphs are updated, with performance guarantees for dag patterns. We experimentally verify that these algorithms scale well, and that the revised notion of graph pattern matching allows us to identify communities commonly found in real-world networks.

UR - http://www.scopus.com/inward/record.url?scp=79960006256&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79960006256&partnerID=8YFLogxK

M3 - Chapter

AN - SCOPUS:79960006256

VL - 3

SP - 264

EP - 275

BT - Proceedings of the VLDB Endowment

ER -