Edge Influence Computation in Dynamic Graphs

Yongrui Qin, Quan Z. Sheng, Simon Parkinson, Nickolas J G Falkner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Reachability queries are of great importance in many research and application areas, including general graph mining, social network analysis and so on. Many approaches have been proposed to compute whether there exists one path from one node to another node in a graph. Most of these approaches focus on static graphs, however in practice dynamic graphs are more common. In this paper, we focus on handling graph reachability queries in dynamic graphs. Specifically we investigate the influence of a given edge in the graph, aiming to study the overall reachability changes in the graph brought by the possible failure/deletion of the edge. To this end, we firstly develop an efficient update algorithm for handling edge deletions. We then define the edge influence concept and put forward a novel computation algorithm to accelerate the computation of edge influence. We evaluate our approach using several real world datasets. The experimental results show that our approach outperforms traditional approaches significantly.

LanguageEnglish
Title of host publicationDatabase Systems for Advanced Applications
Subtitle of host publication22nd International Conference, DASFAA 2017, Suzhou, China, March 27-30, 2017, Proceedings, Part II
EditorsSelçuk Candan, Lei Chen, Torben Bach Pedersen, Lijun Chang, Wen Hua
PublisherSpringer, Cham
Pages649-660
Number of pages12
ISBN (Electronic)9783319556994
ISBN (Print)9783319556987
DOIs
Publication statusPublished - 22 Mar 2017
Event22nd International Conference on Database Systems for Advanced Applications - Suzou, China
Duration: 27 Mar 201730 Mar 2017
Conference number: 22
https://link.springer.com/book/10.1007/978-3-319-55753-3 (Link to Conference Details )

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume10178
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Database Systems for Advanced Applications
Abbreviated titleDASFAA 2017
CountryChina
CitySuzou
Period27/03/1730/03/17
Internet address

Fingerprint

Electric network analysis

Cite this

Qin, Y., Sheng, Q. Z., Parkinson, S., & Falkner, N. J. G. (2017). Edge Influence Computation in Dynamic Graphs. In S. Candan, L. Chen, T. B. Pedersen, L. Chang, & W. Hua (Eds.), Database Systems for Advanced Applications: 22nd International Conference, DASFAA 2017, Suzhou, China, March 27-30, 2017, Proceedings, Part II (pp. 649-660). (Lecture Notes in Computer Science; Vol. 10178). Springer, Cham. https://doi.org/10.1007/978-3-319-55699-4_41
Qin, Yongrui ; Sheng, Quan Z. ; Parkinson, Simon ; Falkner, Nickolas J G. / Edge Influence Computation in Dynamic Graphs. Database Systems for Advanced Applications: 22nd International Conference, DASFAA 2017, Suzhou, China, March 27-30, 2017, Proceedings, Part II. editor / Selçuk Candan ; Lei Chen ; Torben Bach Pedersen ; Lijun Chang ; Wen Hua. Springer, Cham, 2017. pp. 649-660 (Lecture Notes in Computer Science).
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title = "Edge Influence Computation in Dynamic Graphs",
abstract = "Reachability queries are of great importance in many research and application areas, including general graph mining, social network analysis and so on. Many approaches have been proposed to compute whether there exists one path from one node to another node in a graph. Most of these approaches focus on static graphs, however in practice dynamic graphs are more common. In this paper, we focus on handling graph reachability queries in dynamic graphs. Specifically we investigate the influence of a given edge in the graph, aiming to study the overall reachability changes in the graph brought by the possible failure/deletion of the edge. To this end, we firstly develop an efficient update algorithm for handling edge deletions. We then define the edge influence concept and put forward a novel computation algorithm to accelerate the computation of edge influence. We evaluate our approach using several real world datasets. The experimental results show that our approach outperforms traditional approaches significantly.",
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Qin, Y, Sheng, QZ, Parkinson, S & Falkner, NJG 2017, Edge Influence Computation in Dynamic Graphs. in S Candan, L Chen, TB Pedersen, L Chang & W Hua (eds), Database Systems for Advanced Applications: 22nd International Conference, DASFAA 2017, Suzhou, China, March 27-30, 2017, Proceedings, Part II. Lecture Notes in Computer Science, vol. 10178, Springer, Cham, pp. 649-660, 22nd International Conference on Database Systems for Advanced Applications, Suzou, China, 27/03/17. https://doi.org/10.1007/978-3-319-55699-4_41

Edge Influence Computation in Dynamic Graphs. / Qin, Yongrui; Sheng, Quan Z.; Parkinson, Simon; Falkner, Nickolas J G.

Database Systems for Advanced Applications: 22nd International Conference, DASFAA 2017, Suzhou, China, March 27-30, 2017, Proceedings, Part II. ed. / Selçuk Candan; Lei Chen; Torben Bach Pedersen; Lijun Chang; Wen Hua. Springer, Cham, 2017. p. 649-660 (Lecture Notes in Computer Science; Vol. 10178).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - Reachability queries are of great importance in many research and application areas, including general graph mining, social network analysis and so on. Many approaches have been proposed to compute whether there exists one path from one node to another node in a graph. Most of these approaches focus on static graphs, however in practice dynamic graphs are more common. In this paper, we focus on handling graph reachability queries in dynamic graphs. Specifically we investigate the influence of a given edge in the graph, aiming to study the overall reachability changes in the graph brought by the possible failure/deletion of the edge. To this end, we firstly develop an efficient update algorithm for handling edge deletions. We then define the edge influence concept and put forward a novel computation algorithm to accelerate the computation of edge influence. We evaluate our approach using several real world datasets. The experimental results show that our approach outperforms traditional approaches significantly.

AB - Reachability queries are of great importance in many research and application areas, including general graph mining, social network analysis and so on. Many approaches have been proposed to compute whether there exists one path from one node to another node in a graph. Most of these approaches focus on static graphs, however in practice dynamic graphs are more common. In this paper, we focus on handling graph reachability queries in dynamic graphs. Specifically we investigate the influence of a given edge in the graph, aiming to study the overall reachability changes in the graph brought by the possible failure/deletion of the edge. To this end, we firstly develop an efficient update algorithm for handling edge deletions. We then define the edge influence concept and put forward a novel computation algorithm to accelerate the computation of edge influence. We evaluate our approach using several real world datasets. The experimental results show that our approach outperforms traditional approaches significantly.

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Qin Y, Sheng QZ, Parkinson S, Falkner NJG. Edge Influence Computation in Dynamic Graphs. In Candan S, Chen L, Pedersen TB, Chang L, Hua W, editors, Database Systems for Advanced Applications: 22nd International Conference, DASFAA 2017, Suzhou, China, March 27-30, 2017, Proceedings, Part II. Springer, Cham. 2017. p. 649-660. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-319-55699-4_41