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ISMIS
2005
Springer
13 years 10 months ago
Using Supervised Clustering to Enhance Classifiers
Abstract. This paper centers on a novel data mining technique we term supervised clustering. Unlike traditional clustering, supervised clustering is applied to classified examples ...
Christoph F. Eick, Nidal M. Zeidat
ISMIS
2005
Springer
13 years 10 months ago
Getting Computers to See Information Graphics So Users Do Not Have to
Abstract. Information graphics such as bar, line and pie charts appear frequently in electronic media and often contain information that is not found elsewhere in documents. Unfort...
Daniel Chester, Stephanie Elzer
ISMIS
2005
Springer
13 years 10 months ago
A Machine Text-Inspired Machine Learning Approach for Identification of Transmembrane Helix Boundaries
In this paper, we adapt a statistical learning approach, inspired by automated topic segmentation techniques in speech-recognized documents to the challenging protein segmentation ...
Betty Yee Man Cheng, Jaime G. Carbonell, Judith Kl...
ISMIS
2005
Springer
13 years 10 months ago
Scalable Inductive Learning on Partitioned Data
With the rapid advancement of information technology, scalability has become a necessity for learning algorithms to deal with large, real-world data repositories. In this paper, sc...
Qijun Chen, Xindong Wu, Xingquan Zhu
ISMIS
2005
Springer
13 years 10 months ago
The Chisholm Paradox and the Situation Calculus
Deontic logic is appropriate to model a wide variety of legal arguments, however this logic suffers form certain paradoxes of which the so-called Chisholm is one of the most notor...
Robert Demolombe, Maria del Pilar Pozos Parra
ISMIS
2005
Springer
13 years 10 months ago
Mining and Filtering Multi-level Spatial Association Rules with ARES
In spatial data mining, a common task is the discovery of spatial association rules from spatial databases. We propose a distributed system, named ARES that takes advantage of the ...
Annalisa Appice, Margherita Berardi, Michelangelo ...
ISMIS
2005
Springer
13 years 10 months ago
Learning the Daily Model of Network Traffic
Abstract. Anomaly detection is based on profiles that represent normal behaviour of users, hosts or networks and detects attacks as significant deviations from these profiles. In t...
Costantina Caruso, Donato Malerba, Davide Papagni
ISMIS
2005
Springer
13 years 10 months ago
Towards Ad-Hoc Rule Semantics for Gene Expression Data
The notion of rules is very popular and appears in different flavors, for example as association rules in data mining or as functional (or multivalued) dependencies in databases. ...
Marie Agier, Jean-Marc Petit, Einoshin Suzuki
ISMIS
2005
Springer
13 years 10 months ago
Agent-Based Home Simulation and Control
Berardina De Carolis, Giovanni Cozzolongo, Sebasti...