Ranking Outliers Using Symmetric Neighborhood Relationship

  title={Ranking Outliers Using Symmetric Neighborhood Relationship},
  author={Wen Jin and Anthony K. H. Tung and Jiawei Han and Wei Wang},
Mining outliers in database is to find exceptional objects that deviate from the rest of the data set. Besides classical outlier analysis algorithms, recent studies have focused on mining local outliers, i.e., the outliers that have density distribution significantly different from their neighborhood. The estimation of density distribution at the location of an object has so far been based on the density distribution of its k-nearest neighbors [2, 11]. However, when outliers are in the location… CONTINUE READING
Highly Influential
This paper has highly influenced 20 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 234 citations. REVIEW CITATIONS
146 Citations
22 References
Similar Papers


Publications citing this paper.
Showing 1-10 of 146 extracted citations

235 Citations

Citations per Year
Semantic Scholar estimates that this publication has 235 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.

Similar Papers

Loading similar papers…