@inbook{f609adb71bf84ca3bff153968c4401fc,
title = "Reliability in ICA-based text classification",
abstract = "This paper introduces a novel approach for improving the reliability of ICA-based text classifiers, attempting to make the most of the independent components of the text data. In this framework, two issues are adressed: firstly, a relative relevance measure for category assignment is presented. And secondly, a reliability control process is included in the classifier, avoiding the classification of documents belonging to none of the categories defined during the training stage. The experiments have been conducted on a journalistic-style text corpus in Catalan, achieving encouraging results in terms of rejection accuracy. However, similar results are obtained when comparing the proposed relevance measure to the classic magnitude-based technique for category assignment.",
author = "Xavier Sevillano and Francesc Al{\'i}as and Socor{\'o}, {Joan Claudi}",
year = "2004",
doi = "10.1007/978-3-540-30110-3_153",
language = "English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "1213--1220",
editor = "Puntonet, {Carlos G.} and Alberto Prieto",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
address = "Germany",
}