Gateway finder in large graphs: Problem definitions and fast solutions

Hanghang Tong, Spiros Papadimitriou, Christos Faloutsos, Philip S. Yu, Tina Eliassi-Rad

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Given a graph, how to find a small group of 'gateways', that is a small subset of nodes that are crucial in connecting the source to the target? For instance, given a social network, who is the best person to introduce you to, say, Chris Ferguson, the poker champion? Or, given a network of people and skills, who is the best person to help you learn about, say, wavelets? We formally formulate this problem in two scenarios: Pair-Gateway and Group-Gateway. For each scenario, we show that it is sub-modular and thus it can be solved near-optimally. We further give fast, scalable algorithms to find such gateways. Extensive experimental evaluations on real data sets demonstrate the effectiveness and efficiency of the proposed methods.

Original languageEnglish (US)
Pages (from-to)391-411
Number of pages21
JournalInformation Retrieval
Volume15
Issue number3-4
DOIs
StatePublished - Jun 2012
Externally publishedYes

Fingerprint

scenario
human being
small group
social network
efficiency
evaluation
Group

Keywords

  • Gateway
  • Graph mining
  • Scalability
  • Social network
  • Sub-modularity

ASJC Scopus subject areas

  • Information Systems
  • Library and Information Sciences

Cite this

Tong, H., Papadimitriou, S., Faloutsos, C., Yu, P. S., & Eliassi-Rad, T. (2012). Gateway finder in large graphs: Problem definitions and fast solutions. Information Retrieval, 15(3-4), 391-411. https://doi.org/10.1007/s10791-012-9190-3

Gateway finder in large graphs : Problem definitions and fast solutions. / Tong, Hanghang; Papadimitriou, Spiros; Faloutsos, Christos; Yu, Philip S.; Eliassi-Rad, Tina.

In: Information Retrieval, Vol. 15, No. 3-4, 06.2012, p. 391-411.

Research output: Contribution to journalArticle

Tong, H, Papadimitriou, S, Faloutsos, C, Yu, PS & Eliassi-Rad, T 2012, 'Gateway finder in large graphs: Problem definitions and fast solutions', Information Retrieval, vol. 15, no. 3-4, pp. 391-411. https://doi.org/10.1007/s10791-012-9190-3
Tong, Hanghang ; Papadimitriou, Spiros ; Faloutsos, Christos ; Yu, Philip S. ; Eliassi-Rad, Tina. / Gateway finder in large graphs : Problem definitions and fast solutions. In: Information Retrieval. 2012 ; Vol. 15, No. 3-4. pp. 391-411.
@article{bbe094cc10d34e7da23e2c415369ef6a,
title = "Gateway finder in large graphs: Problem definitions and fast solutions",
abstract = "Given a graph, how to find a small group of 'gateways', that is a small subset of nodes that are crucial in connecting the source to the target? For instance, given a social network, who is the best person to introduce you to, say, Chris Ferguson, the poker champion? Or, given a network of people and skills, who is the best person to help you learn about, say, wavelets? We formally formulate this problem in two scenarios: Pair-Gateway and Group-Gateway. For each scenario, we show that it is sub-modular and thus it can be solved near-optimally. We further give fast, scalable algorithms to find such gateways. Extensive experimental evaluations on real data sets demonstrate the effectiveness and efficiency of the proposed methods.",
keywords = "Gateway, Graph mining, Scalability, Social network, Sub-modularity",
author = "Hanghang Tong and Spiros Papadimitriou and Christos Faloutsos and Yu, {Philip S.} and Tina Eliassi-Rad",
year = "2012",
month = "6",
doi = "10.1007/s10791-012-9190-3",
language = "English (US)",
volume = "15",
pages = "391--411",
journal = "Information Retrieval",
issn = "1386-4564",
publisher = "Springer Netherlands",
number = "3-4",

}

TY - JOUR

T1 - Gateway finder in large graphs

T2 - Problem definitions and fast solutions

AU - Tong, Hanghang

AU - Papadimitriou, Spiros

AU - Faloutsos, Christos

AU - Yu, Philip S.

AU - Eliassi-Rad, Tina

PY - 2012/6

Y1 - 2012/6

N2 - Given a graph, how to find a small group of 'gateways', that is a small subset of nodes that are crucial in connecting the source to the target? For instance, given a social network, who is the best person to introduce you to, say, Chris Ferguson, the poker champion? Or, given a network of people and skills, who is the best person to help you learn about, say, wavelets? We formally formulate this problem in two scenarios: Pair-Gateway and Group-Gateway. For each scenario, we show that it is sub-modular and thus it can be solved near-optimally. We further give fast, scalable algorithms to find such gateways. Extensive experimental evaluations on real data sets demonstrate the effectiveness and efficiency of the proposed methods.

AB - Given a graph, how to find a small group of 'gateways', that is a small subset of nodes that are crucial in connecting the source to the target? For instance, given a social network, who is the best person to introduce you to, say, Chris Ferguson, the poker champion? Or, given a network of people and skills, who is the best person to help you learn about, say, wavelets? We formally formulate this problem in two scenarios: Pair-Gateway and Group-Gateway. For each scenario, we show that it is sub-modular and thus it can be solved near-optimally. We further give fast, scalable algorithms to find such gateways. Extensive experimental evaluations on real data sets demonstrate the effectiveness and efficiency of the proposed methods.

KW - Gateway

KW - Graph mining

KW - Scalability

KW - Social network

KW - Sub-modularity

UR - http://www.scopus.com/inward/record.url?scp=84861454556&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84861454556&partnerID=8YFLogxK

U2 - 10.1007/s10791-012-9190-3

DO - 10.1007/s10791-012-9190-3

M3 - Article

AN - SCOPUS:84861454556

VL - 15

SP - 391

EP - 411

JO - Information Retrieval

JF - Information Retrieval

SN - 1386-4564

IS - 3-4

ER -