Co-ranking Authors and Documents in a Heterogeneous Network
D. Zhou, S. Orshanskiy, H. Zha, and C. Giles. ICDM '07: Proceedings of the 2007 Seventh IEEE International Conference on Data Mining, page 739--744. Washington, DC, USA, IEEE Computer Society, (2007)
DOI: 10.1109/ICDM.2007.57
Abstract
Recent graph-theoretic approaches have demonstrated remarkable successes for ranking networked entities, but most of their applications are limited to homogeneous networks such as the network of citations between publications. This paper proposes a novel method for co-ranking authors and their publications using several networks: the social network connecting the authors, the citation network connecting the publications, as well as the authorship network that ties the previous two together. The new co-ranking framework is based on coupling two random walks, that separately rank authors and documents following the PageRank paradigm. As a result, improved rankings of documents and their authors depend on each other in a mutually reinforcing way, thus taking advantage of the additional information implicit in the heterogeneous network of authors and documents.
Description
Co-ranking Authors and Documents in a Heterogeneous Network
%0 Conference Paper
%1 1442053
%A Zhou, Ding
%A Orshanskiy, Sergey A.
%A Zha, Hongyuan
%A Giles, C. Lee
%B ICDM '07: Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
%C Washington, DC, USA
%D 2007
%I IEEE Computer Society
%K MakovChain heterogeneous pagerank
%P 739--744
%R 10.1109/ICDM.2007.57
%T Co-ranking Authors and Documents in a Heterogeneous Network
%U http://portal.acm.org/citation.cfm?id=1442053
%X Recent graph-theoretic approaches have demonstrated remarkable successes for ranking networked entities, but most of their applications are limited to homogeneous networks such as the network of citations between publications. This paper proposes a novel method for co-ranking authors and their publications using several networks: the social network connecting the authors, the citation network connecting the publications, as well as the authorship network that ties the previous two together. The new co-ranking framework is based on coupling two random walks, that separately rank authors and documents following the PageRank paradigm. As a result, improved rankings of documents and their authors depend on each other in a mutually reinforcing way, thus taking advantage of the additional information implicit in the heterogeneous network of authors and documents.
%@ 0-7695-3018-4
@inproceedings{1442053,
abstract = {Recent graph-theoretic approaches have demonstrated remarkable successes for ranking networked entities, but most of their applications are limited to homogeneous networks such as the network of citations between publications. This paper proposes a novel method for co-ranking authors and their publications using several networks: the social network connecting the authors, the citation network connecting the publications, as well as the authorship network that ties the previous two together. The new co-ranking framework is based on coupling two random walks, that separately rank authors and documents following the PageRank paradigm. As a result, improved rankings of documents and their authors depend on each other in a mutually reinforcing way, thus taking advantage of the additional information implicit in the heterogeneous network of authors and documents.},
added-at = {2010-03-29T16:05:05.000+0200},
address = {Washington, DC, USA},
author = {Zhou, Ding and Orshanskiy, Sergey A. and Zha, Hongyuan and Giles, C. Lee},
biburl = {https://www.bibsonomy.org/bibtex/2b507738eacca71c80396e18263c29a6c/zhenzhenx},
booktitle = {ICDM '07: Proceedings of the 2007 Seventh IEEE International Conference on Data Mining},
description = {Co-ranking Authors and Documents in a Heterogeneous Network},
doi = {10.1109/ICDM.2007.57},
interhash = {01c44531daf1f7e7c5fc6a960ea5a76c},
intrahash = {b507738eacca71c80396e18263c29a6c},
isbn = {0-7695-3018-4},
keywords = {MakovChain heterogeneous pagerank},
pages = {739--744},
publisher = {IEEE Computer Society},
timestamp = {2010-06-16T11:05:42.000+0200},
title = {Co-ranking Authors and Documents in a Heterogeneous Network},
url = {http://portal.acm.org/citation.cfm?id=1442053},
year = 2007
}