Co-ranking authors and documents in a heterogeneous network

Ding Zhou, Sergey A. Orshanskiy, Hongyuan Zha, C. Lee Giles

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

151 Citations (Scopus)

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.

Original languageEnglish (US)
Title of host publicationProceedings of the 7th IEEE International Conference on Data Mining, ICDM 2007
Pages739-744
Number of pages6
DOIs
StatePublished - Dec 1 2007
Event7th IEEE International Conference on Data Mining, ICDM 2007 - Omaha, NE, United States
Duration: Oct 28 2007Oct 31 2007

Publication series

NameProceedings - IEEE International Conference on Data Mining, ICDM
ISSN (Print)1550-4786

Other

Other7th IEEE International Conference on Data Mining, ICDM 2007
CountryUnited States
CityOmaha, NE
Period10/28/0710/31/07

Fingerprint

Heterogeneous networks

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Zhou, D., Orshanskiy, S. A., Zha, H., & Giles, C. L. (2007). Co-ranking authors and documents in a heterogeneous network. In Proceedings of the 7th IEEE International Conference on Data Mining, ICDM 2007 (pp. 739-744). [4470320] (Proceedings - IEEE International Conference on Data Mining, ICDM). https://doi.org/10.1109/ICDM.2007.57
Zhou, Ding ; Orshanskiy, Sergey A. ; Zha, Hongyuan ; Giles, C. Lee. / Co-ranking authors and documents in a heterogeneous network. Proceedings of the 7th IEEE International Conference on Data Mining, ICDM 2007. 2007. pp. 739-744 (Proceedings - IEEE International Conference on Data Mining, ICDM).
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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.",
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Zhou, D, Orshanskiy, SA, Zha, H & Giles, CL 2007, Co-ranking authors and documents in a heterogeneous network. in Proceedings of the 7th IEEE International Conference on Data Mining, ICDM 2007., 4470320, Proceedings - IEEE International Conference on Data Mining, ICDM, pp. 739-744, 7th IEEE International Conference on Data Mining, ICDM 2007, Omaha, NE, United States, 10/28/07. https://doi.org/10.1109/ICDM.2007.57

Co-ranking authors and documents in a heterogeneous network. / Zhou, Ding; Orshanskiy, Sergey A.; Zha, Hongyuan; Giles, C. Lee.

Proceedings of the 7th IEEE International Conference on Data Mining, ICDM 2007. 2007. p. 739-744 4470320 (Proceedings - IEEE International Conference on Data Mining, ICDM).

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

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AB - 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.

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Zhou D, Orshanskiy SA, Zha H, Giles CL. Co-ranking authors and documents in a heterogeneous network. In Proceedings of the 7th IEEE International Conference on Data Mining, ICDM 2007. 2007. p. 739-744. 4470320. (Proceedings - IEEE International Conference on Data Mining, ICDM). https://doi.org/10.1109/ICDM.2007.57