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Three-hop distance estimation in social graphs.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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Three-hop distance estimation in social graphs. / Welke, Pascal; Markowetz, Alexander; Suel, Torsten et al.
Three-hop distance estimation in social graphs.. IEEE, 2016. p. 1048-1055.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Welke, P, Markowetz, A, Suel, T & Christoforaki, M 2016, Three-hop distance estimation in social graphs. in Three-hop distance estimation in social graphs.. IEEE, pp. 1048-1055, 2016 IEEE International Conference on Big Data (Big Data), Washington, DC, 5/12/16. https://doi.org/10.1109/BIGDATA.2016.7840706

APA

Welke, P., Markowetz, A., Suel, T., & Christoforaki, M. (2016). Three-hop distance estimation in social graphs. In Three-hop distance estimation in social graphs. (pp. 1048-1055). IEEE. https://doi.org/10.1109/BIGDATA.2016.7840706

Vancouver

Welke P, Markowetz A, Suel T, Christoforaki M. Three-hop distance estimation in social graphs. In Three-hop distance estimation in social graphs.. IEEE. 2016. p. 1048-1055 doi: 10.1109/BIGDATA.2016.7840706

Author

Welke, Pascal ; Markowetz, Alexander ; Suel, Torsten et al. / Three-hop distance estimation in social graphs. Three-hop distance estimation in social graphs.. IEEE, 2016. pp. 1048-1055

Bibtex

@inproceedings{37f4fd4a6a034ce1953d0530c87b1bd7,
title = "Three-hop distance estimation in social graphs.",
abstract = "In this paper, we study a 3-hop approach to distance estimation that uses two intermediate landmarks, where each landmark only stores distances to vertices in its local neighborhood and to the other landmarks. We show how to suitably represent and compress the distance data stored for each landmark, for the 2-hop and 3-hop case. Overall, we find that 3-hop methods achieve modest but promising improvement in some cases, while being comparable or slightly worse than 2-hop methods in others. Furthermore, our light compression schemes improve the practical applicability of both the 2-hop and 3-hop methods.",
author = "Pascal Welke and Alexander Markowetz and Torsten Suel and Maria Christoforaki",
note = "DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.; 2016 IEEE International Conference on Big Data (Big Data) ; Conference date: 05-12-2016 Through 08-12-2016",
year = "2016",
month = dec,
day = "5",
doi = "10.1109/BIGDATA.2016.7840706",
language = "Undefined/Unknown",
isbn = "9781467390064",
pages = "1048--1055",
booktitle = "Three-hop distance estimation in social graphs.",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - Three-hop distance estimation in social graphs.

AU - Welke, Pascal

AU - Markowetz, Alexander

AU - Suel, Torsten

AU - Christoforaki, Maria

N1 - DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

PY - 2016/12/5

Y1 - 2016/12/5

N2 - In this paper, we study a 3-hop approach to distance estimation that uses two intermediate landmarks, where each landmark only stores distances to vertices in its local neighborhood and to the other landmarks. We show how to suitably represent and compress the distance data stored for each landmark, for the 2-hop and 3-hop case. Overall, we find that 3-hop methods achieve modest but promising improvement in some cases, while being comparable or slightly worse than 2-hop methods in others. Furthermore, our light compression schemes improve the practical applicability of both the 2-hop and 3-hop methods.

AB - In this paper, we study a 3-hop approach to distance estimation that uses two intermediate landmarks, where each landmark only stores distances to vertices in its local neighborhood and to the other landmarks. We show how to suitably represent and compress the distance data stored for each landmark, for the 2-hop and 3-hop case. Overall, we find that 3-hop methods achieve modest but promising improvement in some cases, while being comparable or slightly worse than 2-hop methods in others. Furthermore, our light compression schemes improve the practical applicability of both the 2-hop and 3-hop methods.

U2 - 10.1109/BIGDATA.2016.7840706

DO - 10.1109/BIGDATA.2016.7840706

M3 - Conference contribution/Paper

SN - 9781467390064

SP - 1048

EP - 1055

BT - Three-hop distance estimation in social graphs.

PB - IEEE

T2 - 2016 IEEE International Conference on Big Data (Big Data)

Y2 - 5 December 2016 through 8 December 2016

ER -