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KDD
2007
ACM
141views Data Mining» more  KDD 2007»
14 years 9 months ago
Detecting anomalous records in categorical datasets
We consider the problem of detecting anomalies in high arity categorical datasets. In most applications, anomalies are defined as data points that are 'abnormal'. Quite ...
Kaustav Das, Jeff G. Schneider
KDD
2006
ACM
109views Data Mining» more  KDD 2006»
14 years 9 months ago
Extracting redundancy-aware top-k patterns
Observed in many applications, there is a potential need of extracting a small set of frequent patterns having not only high significance but also low redundancy. The significance...
Dong Xin, Hong Cheng, Xifeng Yan, Jiawei Han
KDD
2004
ACM
131views Data Mining» more  KDD 2004»
14 years 9 months ago
Fast nonlinear regression via eigenimages applied to galactic morphology
Astronomy increasingly faces the issue of massive datasets. For instance, the Sloan Digital Sky Survey (SDSS) has so far generated tens of millions of images of distant galaxies, ...
Brigham Anderson, Andrew W. Moore, Andrew Connolly...
KDD
2004
ACM
144views Data Mining» more  KDD 2004»
14 years 9 months ago
IncSpan: incremental mining of sequential patterns in large database
Many real life sequence databases, such as customer shopping sequences, medical treatment sequences, etc., grow incrementally. It is undesirable to mine sequential patterns from s...
Hong Cheng, Xifeng Yan, Jiawei Han
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
14 years 9 months ago
Machine learning for online query relaxation
In this paper we provide a fast, data-driven solution to the failing query problem: given a query that returns an empty answer, how can one relax the query's constraints so t...
Ion Muslea