Robust reputation-based ranking on bipartite rating networks

Rong Hua Li, Jeffery Xu Yu, Xin Huang, Hong Cheng

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

68 Citations (Scopus)


With the growth of the Internet and E-commerce, bi- partite rating networks are ubiquitous. In such bipar- Tite rating networks, there exist two types of entities: The users and the objects, where users give ratings to objects. A fundamental problem in such networks is how to rank the objects by user's ratings. Although it has been extensively studied in the past decade, the ex- isting algorithms either cannot guarantee convergence, or are not robust to the spammers. In this paper, we propose six new reputation-based algorithms, where the users' reputation is determined by the aggregated differ- ence between the users' ratings and the corresponding objects' rankings. We prove that all of our algorithms converge into a unique fixed point. The time and space complexity of our algorithms are linear w.r.t. the size of the graph, thus they can be scalable to large datasets. Moreover, our algorithms are robust to the spamming users. We evaluate our algorithms using three real datasets. The experimental results confirm the effec- Tiveness, efficiency, and robustness of our algorithms.

Original languageEnglish
Title of host publicationProceedings of the 12th SIAM International Conference on Data Mining, SDM 2012
EditorsJoydeep Ghosh, Huan Liu, Ian Davidson, Carlotta Domeniconi, Chandrika Kamath
PublisherSociety for Industrial and Applied Mathematics (SIAM)
Number of pages12
ISBN (Electronic)9781611972825
ISBN (Print)9781611972320
Publication statusPublished - Apr 2012
Event12th SIAM International Conference on Data Mining, SDM 2012 - Anaheim, CA, United States
Duration: 26 Apr 201228 Apr 2012

Publication series

NameProceedings of the 12th SIAM International Conference on Data Mining, SDM 2012


Conference12th SIAM International Conference on Data Mining, SDM 2012
Country/TerritoryUnited States
CityAnaheim, CA
Internet address

Scopus Subject Areas

  • Computer Science Applications


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