A spectral framework for detecting inconsistency across multi-source object relationships

Jing Gao, Wei Fan, Deepak Turaga, Srinivasan Parthasarathy, Jiawei Han

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

Abstract

In this paper, we propose to conduct anomaly detection across multiple sources to identify objects that have inconsistent behavior across these sources.We assume that a set of objects can be described from various perspectives (multiple information sources). The underlying clustering structure of normal objects is usually shared by multiple sources. However, anomalous objects belong to different clusters when considering different aspects. For example, there exist movies that are expected to be liked by kids by genre, but are liked by grown-ups based on user viewing history. To identify such objects, we propose to compute the distance between different eigen decomposition results of the same object with respect to different sources as its anomalous score. We also give interpretations from the perspectives of constrained spectral clustering and random walks over graph. Experimental results on several UCI as well as DBLP and MovieLens datasets demonstrate the effectiveness of the proposed approach.

Original languageEnglish (US)
Title of host publicationProceedings - 11th IEEE International Conference on Data Mining, ICDM 2011
Pages1050-1055
Number of pages6
DOIs
StatePublished - 2011
Event11th IEEE International Conference on Data Mining, ICDM 2011 - Vancouver, BC, Canada
Duration: Dec 11 2011Dec 14 2011

Publication series

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

Other

Other11th IEEE International Conference on Data Mining, ICDM 2011
CountryCanada
CityVancouver, BC
Period12/11/1112/14/11

Keywords

  • Anomaly detection
  • Multiple information sources
  • Spectral methods

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Gao, J., Fan, W., Turaga, D., Parthasarathy, S., & Han, J. (2011). A spectral framework for detecting inconsistency across multi-source object relationships. In Proceedings - 11th IEEE International Conference on Data Mining, ICDM 2011 (pp. 1050-1055). [6137313] (Proceedings - IEEE International Conference on Data Mining, ICDM). https://doi.org/10.1109/ICDM.2011.16