@inbook{9c6d82db762d4ad39d851e28eab85869,
title = "Combining Multiclass Maximum Entropy Text Classifiers with Neural Network Voting",
abstract = "We improve a high-accuracy maximum entropy classifier by combining an ensemble of classifiers with neural network voting. In our experiments we demonstrate significantly superior performance both over a single classifier as well as over the use of the traditional weighted-sum voting approach. Specifically, we apply this to a maximum entropy classifier on a large scale multi-class text categorization task: the online job directory Flipdog with over half a million jobs in 65 categories.",
author = "Philipp Koehn",
year = "2002",
doi = "10.1007/3-540-45433-0_19",
language = "English",
isbn = "978-3-540-43829-8",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "125--131",
editor = "Elisabete Ranchhod and Mamede, {Nuno J.}",
booktitle = "Advances in Natural Language Processing",
address = "United Kingdom",
note = "Third International Conference PorTAL 2002 ; Conference date: 23-06-2002 Through 26-06-2002",
}