Boosting PageRank Scores by Optimizing Internal Link Structure

Naoto Ohsaka, Tomohiro Sonobe, Naonori Kakimura, Takuro Fukunaga, Sumio Fujita, Ken ichi Kawarabayashi

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

1 Citation (Scopus)

Abstract

We consider and formulate problems of PageRank score boosting motivated by applications such as effective web advertising. More precisely, given a graph and target vertices, one is required to find a fixed-size set of missing edges that maximizes the minimum PageRank score among the targets. We provide theoretical analyses to show that all of them are NP-hard. To overcome the hardness, we develop heuristic-based algorithms for them. We finally perform experiments on several real-world networks to verify the effectiveness of the proposed algorithms compared to baselines. Specifically, our algorithm achieves 100 times improvements of the minimum PageRank score among selected 100 vertices by adding only dozens of edges.

Original languageEnglish
Title of host publicationDatabase and Expert Systems Applications - 29th International Conference, DEXA 2018, Proceedings
EditorsHui Ma, Roland R. Wagner, Sven Hartmann, Gunther Pernul, Abdelkader Hameurlain
PublisherSpringer Verlag
Pages424-439
Number of pages16
ISBN (Print)9783319988085
DOIs
Publication statusPublished - 2018 Jan 1
Event29th International Conference on Database and Expert Systems Applications, DEXA 2018 - Regensburg, Germany
Duration: 2018 Sep 32018 Sep 6

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11029 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other29th International Conference on Database and Expert Systems Applications, DEXA 2018
CountryGermany
CityRegensburg
Period18/9/318/9/6

Fingerprint

PageRank
Boosting
Internal
Target
Hardness
Marketing
Baseline
NP-complete problem
Maximise
Heuristics
Verify
Graph in graph theory
Experiment
Experiments

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Ohsaka, N., Sonobe, T., Kakimura, N., Fukunaga, T., Fujita, S., & Kawarabayashi, K. I. (2018). Boosting PageRank Scores by Optimizing Internal Link Structure. In H. Ma, R. R. Wagner, S. Hartmann, G. Pernul, & A. Hameurlain (Eds.), Database and Expert Systems Applications - 29th International Conference, DEXA 2018, Proceedings (pp. 424-439). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11029 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-98809-2_26

Boosting PageRank Scores by Optimizing Internal Link Structure. / Ohsaka, Naoto; Sonobe, Tomohiro; Kakimura, Naonori; Fukunaga, Takuro; Fujita, Sumio; Kawarabayashi, Ken ichi.

Database and Expert Systems Applications - 29th International Conference, DEXA 2018, Proceedings. ed. / Hui Ma; Roland R. Wagner; Sven Hartmann; Gunther Pernul; Abdelkader Hameurlain. Springer Verlag, 2018. p. 424-439 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11029 LNCS).

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

Ohsaka, N, Sonobe, T, Kakimura, N, Fukunaga, T, Fujita, S & Kawarabayashi, KI 2018, Boosting PageRank Scores by Optimizing Internal Link Structure. in H Ma, RR Wagner, S Hartmann, G Pernul & A Hameurlain (eds), Database and Expert Systems Applications - 29th International Conference, DEXA 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11029 LNCS, Springer Verlag, pp. 424-439, 29th International Conference on Database and Expert Systems Applications, DEXA 2018, Regensburg, Germany, 18/9/3. https://doi.org/10.1007/978-3-319-98809-2_26
Ohsaka N, Sonobe T, Kakimura N, Fukunaga T, Fujita S, Kawarabayashi KI. Boosting PageRank Scores by Optimizing Internal Link Structure. In Ma H, Wagner RR, Hartmann S, Pernul G, Hameurlain A, editors, Database and Expert Systems Applications - 29th International Conference, DEXA 2018, Proceedings. Springer Verlag. 2018. p. 424-439. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-98809-2_26
Ohsaka, Naoto ; Sonobe, Tomohiro ; Kakimura, Naonori ; Fukunaga, Takuro ; Fujita, Sumio ; Kawarabayashi, Ken ichi. / Boosting PageRank Scores by Optimizing Internal Link Structure. Database and Expert Systems Applications - 29th International Conference, DEXA 2018, Proceedings. editor / Hui Ma ; Roland R. Wagner ; Sven Hartmann ; Gunther Pernul ; Abdelkader Hameurlain. Springer Verlag, 2018. pp. 424-439 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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