We present a supervised machine learning algorithm for metonymy resolution, which exploits the similarity between examples of conventional metonymy. We show that syntactic head-mo...
Abstract--In this paper we investigate the sparsity and recognition capabilities of two approximate Bayesian classification algorithms, the multi-class multi-kernel Relevance Vecto...
Ioannis Psorakis, Theodoros Damoulas, Mark A. Giro...
This paper aims to address the problem of anomaly detection and discrimination in complex behaviours, where anomalies are subtle and difficult to detect owing to the complex tempor...
Similarity search in database systems is becoming an increasingly important task in modern application domains such as multimedia, molecular biology, medical imaging, computer aid...
Stefan Brecheisen, Hans-Peter Kriegel, Peer Kr&oum...
Distributed object architectures and Java are important for building modern, scalable, web-enabled applications. This paper is focused on qualitative and quantitative comparison o...