%0 Conference Paper %1 zhou2007coranking %A Zhou, Ding %A Orshanskiy, S.A. %A Zha, Hongyuan %A Giles, C.L. %B Data Mining, 2007. ICDM 2007. Seventh IEEE International Conference on %D 2007 %K multigraph pagerank %P 739 -744 %R 10.1109/ICDM.2007.57 %T Co-ranking Authors and Documents in a Heterogeneous Network %U http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4470320&tag=1 %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 PageRankparadigm. 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.

@inproceedings{zhou2007coranking, 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 PageRankparadigm. 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 = {2013-02-14T13:56:29.000+0100}, author = {Zhou, Ding and Orshanskiy, S.A. and Zha, Hongyuan and Giles, C.L.}, biburl = {https://www.bibsonomy.org/bibtex/295afc76fe3d0cdbc12ce2b50123e9dce/folke}, booktitle = {Data Mining, 2007. ICDM 2007. Seventh IEEE International Conference on}, description = {IEEE Xplore - Co-ranking Authors and Documents in a Heterogeneous Network}, doi = {10.1109/ICDM.2007.57}, interhash = {01c44531daf1f7e7c5fc6a960ea5a76c}, intrahash = {95afc76fe3d0cdbc12ce2b50123e9dce}, issn = {1550-4786}, keywords = {multigraph pagerank}, month = {oct.}, pages = {739 -744}, timestamp = {2013-02-14T13:56:29.000+0100}, title = {Co-ranking Authors and Documents in a Heterogeneous Network}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4470320&tag=1}, year = 2007 }