Document classification on neural networks using only positive examples (poster session)

Authors:
Larry M. Manevitz;Malik Yousef
Affiliations:
Department of Computer Science, University of Haifa, Haifa, Israel;Department of Computer Science, University of Haifa, Haifa, Israel
Venue:
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Year:
2000

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Abstract

In this paper, we show how a simple feed-forward neural network can be trained to filter documents when only positive information is available, and that this method seems to be superior to more standard methods, such as tf-idf retrieval based on an “average vector”. A novel experimental finding that retrieval is enhanced substantially in this context by carrying out a certain kind of uniform transformation (“Hadamard”) of the information prior to the training of the network.