Abstract. Feature selection refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encountered in many areas such as machine...
Abstract. Global integration and migration force people to learn additional languages. With respect to major languages, the acquisition is already initiated at primary school but a...
Oliver Jokisch, Uwe Koloska, Diane Hirschfeld, R&u...
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
Document clustering has long been an important problem in information retrieval. In this paper, we present a new clustering algorithm ASI1, which uses explicitly modeling of the s...
Abstract. We propose a novel framework named Hidden Colored PetriNet for Alert Correlation and Understanding (HCPN-ACU) in intrusion detection system. This model is based upon the ...