Abstract--We participated (as Team 9) in the Article Classification Task of the Biocreative II.5 Challenge: binary classification of fulltext documents relevant for protein-protein...
Abstract. This paper proposes a novel solution to spam detection inspired by a model of the adaptive immune system known as the crossregulation model. We report on the testing of a...
Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competit...
Suppose that the only available information in a multi-class problem are expert estimates of the conditional probabilities of occurrence for a set of binary features. The aim is t...
Ludmila I. Kuncheva, Christopher J. Whitaker, Pete...
In this paper, we present an automated text classification system for the classification of biomedical papers. This classification is based on whether there is experimental eviden...
Min Shi, David S. Edwin, Rakesh Menon, Lixiang She...
This study aims at identifying when an event written in text occurs. In particular, we classify a sentence for an event into four time-slots; morning, daytime, evening, and night....
Abstract. We investigate a generative latent variable model for modelbased word saliency estimation for text modelling and classification. The estimation algorithm derived is able ...
BAYDA is a software package for flexible data analysis in predictive data mining tasks. The mathematical model underlying the program is based on a simple Bayesian network, the Na...
Extracting and processing information from web pages is an important task in many areas like constructing search engines, information retrieval, and data mining from the Web. Comm...
Milos Kovacevic, Michelangelo Diligenti, Marco Gor...