In this paper we propose a methodology to learn to extract domain-specific information from large repositories (e.g. the Web) with minimum user intervention. Learning is seeded b...
Fabio Ciravegna, Alexiei Dingli, David Guthrie, Yo...
Background: Unsupervised annotation of proteins by software pipelines suffers from very high error rates. Spurious functional assignments are usually caused by unwarranted homolog...
Irena I. Artamonova, Goar Frishman, Dmitrij Frishm...
Abstract. Relational database systems are becoming increasingly popular in the scientific community to support the interactive exploration of large volumes of data. In this scenar...
Today many applications routinely generate large quantities of data. The data often takes the form of (time) series, or more generally streams, i.e. an ordered sequence of records...
In solving the classification problem in relational data mining, traditional methods, for example, the C4.5 and its variants, usually require data transformations from datasets sto...