@inproceedings{6f67b0c2b85b432a9f409ec6234642d9,
title = "High-performance knowledge extraction from data on PC-based networks of workstations",
abstract = "The automatic construction of classifiers (programs able to correctly classify data collected from the real world) is one of the major problems in pattern recognition and in a wide area related to Artificial Intelligence, including Data Mining. In this paper we present G-Net, a distributed algorithm able to infer classifiers from pre-collected data, and its implementation on PC-based Networks of Workstations (PC-NOWs). In order to effectively exploit the computing power provided by PCNOWs, G-Net incorporates a set of dynamic load distribution techniques that allow it to adapt its behavior to variations in the computing power due to resource contention. Moreover, it is provided with a fault tolerance scheme that enables it to continue its computation even if the majority of the machines become unavailable during its execution.",
author = "Cosimo Anglano and Attilio Giordana and {Lo Bello}, Giuseppe",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 1999.; 13th International Parallel Processing Symposium, IPPS 1999 Held in Conjunction with the 10th Symposium on Parallel and Distributed Processing, SPDP 1999 ; Conference date: 12-04-1999 Through 16-04-1999",
year = "1999",
doi = "10.1007/BFb0097998",
language = "English",
isbn = "3540658319",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "1131--1144",
editor = "Jos{\'e} Rolim",
booktitle = "Parallel and Distributed Processing - 11 th IPPS/SPDP 1999 Workshops Held in Conjunction with the 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing, Proceedings",
address = "Germany",
}