D. Liben-Nowell, and J. Kleinberg. Proceedings of the 12th International Conference on Information and Knowledge Management (CIKM 2003), page 556--559. New Orleans, LA, USA, ACM, (2003)
DOI: 10.1145/956863.956972
Abstract
Given a snapshot of a social network, can we infer which new interactions among its members are likely to occur in the near future? We formalize this question as the <i>link prediction problem</i>, and develop approaches to link prediction based on measures the "proximity" of nodes in a network. Experiments on large co-authorship networks suggest that information about future interactions can be extracted from network topology alone, and that fairly subtle measures for detecting node proximity can outperform more direct measures.
%0 Conference Paper
%1 libennowell2003
%A Liben-Nowell, David
%A Kleinberg, Jon
%B Proceedings of the 12th International Conference on Information and Knowledge Management (CIKM 2003)
%C New Orleans, LA, USA
%D 2003
%I ACM
%K mining ontology
%P 556--559
%R 10.1145/956863.956972
%T The link prediction problem for social networks
%U http://doi.acm.org/10.1145/956863.956972
%X Given a snapshot of a social network, can we infer which new interactions among its members are likely to occur in the near future? We formalize this question as the <i>link prediction problem</i>, and develop approaches to link prediction based on measures the "proximity" of nodes in a network. Experiments on large co-authorship networks suggest that information about future interactions can be extracted from network topology alone, and that fairly subtle measures for detecting node proximity can outperform more direct measures.
%@ 1-58113-723-0
@inproceedings{libennowell2003,
abstract = {Given a snapshot of a social network, can we infer which new interactions among its members are likely to occur in the near future? We formalize this question as the <i>link prediction problem</i>, and develop approaches to link prediction based on measures the "proximity" of nodes in a network. Experiments on large co-authorship networks suggest that information about future interactions can be extracted from network topology alone, and that fairly subtle measures for detecting node proximity can outperform more direct measures.},
acmid = {956972},
added-at = {2011-10-04T16:05:59.000+0200},
address = {New Orleans, LA, USA},
author = {Liben-Nowell, David and Kleinberg, Jon},
biburl = {https://www.bibsonomy.org/bibtex/29f8ec51fbfae73031031041396fec1e7/utahell},
booktitle = {Proceedings of the 12th International Conference on Information and Knowledge Management (CIKM 2003)},
description = {The link prediction problem for social networks},
doi = {10.1145/956863.956972},
interhash = {1920da9fec5905f031a0ab3919553362},
intrahash = {9f8ec51fbfae73031031041396fec1e7},
isbn = {1-58113-723-0},
keywords = {mining ontology},
location = {New Orleans, LA, USA},
numpages = {4},
pages = {556--559},
publisher = {ACM},
timestamp = {2011-12-16T15:32:21.000+0100},
title = {The link prediction problem for social networks},
url = {http://doi.acm.org/10.1145/956863.956972},
year = 2003
}