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- Title
SLOM: a new measure for local spatial outliers.
- Authors
Chawla, Sanjay; Pei Sun
- Abstract
We propose a measure, spatial local outlier measure (SLOM), which captures the local behaviour of datum in their spatial neighbourhood. With the help of SLOM, we are able to discern local spatial outliers that are usually missed by global techniques, like “three standard deviations away from the mean”. Furthermore, the measure takes into account the local stability around a data point and suppresses the reporting of outliers in highly unstable areas, where data are too heterogeneous and the notion of outliers is not meaningful. We prove several properties of SLOM and report experiments on synthetic and real data sets that show that our approach is novel and scalable to large datasets.
- Subjects
STANDARD deviations; DATA mining; DATABASES; HETEROGENEOUS computing; AIR pressure
- Publication
Knowledge & Information Systems, 2006, Vol 9, Issue 4, p412
- ISSN
0219-1377
- Publication type
Article
- DOI
10.1007/s10115-005-0200-2