KDD
2005
ACM
14 years 9 months ago
2005
ACM
While scalable data mining methods are expected to cope with massive Web data, coping with evolving trends in noisy data in a continuous fashion, and without any unnecessary stopp...
KDD
2005
ACM
14 years 9 months ago
2005
ACM
Knowledge Discovery in time series usually requires symbolic time series. Many discretization methods that convert numeric time series to symbolic time series ignore the temporal ...
KDD
2005
ACM
14 years 9 months ago
2005
ACM
Temporal Text Mining (TTM) is concerned with discovering temporal patterns in text information collected over time. Since most text information bears some time stamps, TTM has man...
KDD
2005
ACM
14 years 9 months ago
2005
ACM
Many classification tasks, such as spam filtering, intrusion detection, and terrorism detection, are complicated by an adversary who wishes to avoid detection. Previous work on ad...
KDD
2005
ACM
14 years 9 months ago
2005
ACM
Dyadic data matrices, such as co-occurrence matrix, rating matrix, and proximity matrix, arise frequently in various important applications. A fundamental problem in dyadic data a...
KDD
2005
ACM
14 years 9 months ago
2005
ACM
In this paper, we discuss a problem of finding risk patterns in medical data. We define risk patterns by a statistical metric, relative risk, which has been widely used in epidemi...
KDD
2005
ACM
14 years 9 months ago
2005
ACM
How do real graphs evolve over time? What are "normal" growth patterns in social, technological, and information networks? Many studies have discovered patterns in stati...
KDD
2005
ACM
14 years 9 months ago
2005
ACM
In the paper we show that diagnostic classes in cancer gene expression data sets, which most often include thousands of features (genes), may be effectively separated with simple ...
KDD
2005
ACM
14 years 9 months ago
2005
ACM
KDD
2005
ACM
14 years 9 months ago
2005
ACM
In this paper, we show that stylistic text features can be exploited to determine an anonymous author's native language with high accuracy. Specifically, we first use automat...