We propose a method for induction of compact optimal recommendation policies based on discovery of frequent itemsets in a purchase database, followed by the application of standar...
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
This paper is concerned with the problem of Imbalanced Classification (IC) in web mining, which often arises on the web due to the "Matthew Effect". As web IC applicatio...
Knowledge Discovery in Databases (KDD), also known as data mining, focuses on the computerized exploration of large amounts of data and on the discovery of interesting patterns wi...
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...