Latent business networks mining : A probabilistic generative model

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

4 Scopus Citations
View graph of relations

Author(s)

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings - 2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012
Pages558-562
Publication statusPublished - 2012

Conference

Title2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012
PlaceChina
CityMacau
Period4 - 7 December 2012

Abstract

Though numerous research has been devoted to social network discovery and analysis, relatively little research has been conducted on business network discovery. The main contribution of our research is the development of a novel probabilistic generative model for latent business networks mining. Our experimental results confirm that the proposed method outperforms the well-known vector space based model by 24% in terms of AUC value. © 2012 IEEE.

Research Area(s)

  • Business Networks Mining, Latent Dirichlet Allocation, Semi-supervised Machine Learning, Web Intelligence

Citation Format(s)

Latent business networks mining: A probabilistic generative model. / Zhang, Wenping; Lau, Raymond Y.K.; Xia, Yunqing et al.
Proceedings - 2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012. 2012. p. 558-562 6511940.

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review