OTM
2009
Springer
14 years 5 months ago
2009
Springer
Abstract. We present a method for using aligned ontologies to merge taxonomically organized data sets that have apparently compatible schemas, but potentially different semantics f...
IPOM
2009
Springer
14 years 5 months ago
2009
Springer
Abstract. Flow-based intrusion detection has recently become a promising security mechanism in high speed networks (1-10 Gbps). Despite the richness in contributions in this field...
GBRPR
2009
Springer
14 years 5 months ago
2009
Springer
The collection of behavior protocols is a common practice in human factors research, but the analysis of these large data sets has always been a tedious and time-consuming process....
EMO
2009
Springer
14 years 5 months ago
2009
Springer
When training Support Vector Machine (SVM), selection of a training data set becomes an important issue, since the problem of overfitting exists with a large number of training da...
DEXA
2009
Springer
14 years 5 months ago
2009
Springer
We solve the problem of record linkage between databases where record fields are mixed and permuted in different ways. The solution method uses a conditional random fields model...
WSOM
2009
Springer
14 years 5 months ago
2009
Springer
Abstract. SOMs have proven to be a very powerful tool for data analysis. However, comparing multiple SOMs trained on the same data set using different parameters or initialisation...
ICASSP
2009
IEEE
14 years 5 months ago
2009
IEEE
This paper proposes a new approach to the challenging open-set language detection task. Most state-of-the-art approaches make use of data sources with several out-of-set languages...
EDBT
2009
ACM
14 years 5 months ago
2009
ACM
Privacy models such as k-anonymity and -diversity typically offer an aggregate or scalar notion of the privacy property that holds collectively on the entire anonymized data set....
KDD
2008
ACM
14 years 11 months ago
2008
ACM
Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
ICDT
2009
ACM
14 years 11 months ago
2009
ACM
Partitioning is an important step in several database algorithms, including sorting, aggregation, and joins. Partitioning is also fundamental for dividing work into equal-sized (o...