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ECCV
2010
Springer
13 years 10 months ago
Clustering Complex Data with Group-Dependent Feature Selection
Abstract. We describe a clustering approach with the emphasis on detecting coherent structures in a complex dataset, and illustrate its effectiveness with computer vision applicat...
ACL
2006
13 years 9 months ago
Answer Extraction, Semantic Clustering, and Extractive Summarization for Clinical Question Answering
This paper presents a hybrid approach to question answering in the clinical domain that combines techniques from summarization and information retrieval. We tackle a frequently-oc...
Dina Demner-Fushman, Jimmy J. Lin
BMCBI
2008
122views more  BMCBI 2008»
13 years 7 months ago
A practical comparison of two K-Means clustering algorithms
Background: Data clustering is a powerful technique for identifying data with similar characteristics, such as genes with similar expression patterns. However, not all implementat...
Gregory A. Wilkin, Xiuzhen Huang
CEC
2008
IEEE
14 years 2 months ago
An approach to intrusion detection by means of idiotypic networks paradigm
Abstract— In this paper we present a novel intrusion detection architecture based on Idiotypic Network Theory (INIDIS), that aims at dealing with large scale network attacks feat...
Marek Ostaszewski, Pascal Bouvry, Franciszek Sered...
PRIB
2009
Springer
135views Bioinformatics» more  PRIB 2009»
14 years 2 months ago
Sequential Hierarchical Pattern Clustering
Abstract. Clustering is a widely used unsupervised data analysis technique in machine learning. However, a common requirement amongst many existing clustering methods is that all p...
Bassam Farran, Amirthalingam Ramanan, Mahesan Nira...