Abstract
The training of feedforward neural networks for document filtering was discussed with respect to availability of positive information. A filter was developed for the search of the required document in a corpus of documents. A three-level feedforward neural network with a `bottleneck' was employed under standard back-propagation for learning the identity function. The term-frequency-inverse-document-frequency (tf-idf) and Hadamard product representations were employed for the implementation of the bottleneck filter.
| Original language | English |
|---|---|
| Pages (from-to) | 304-306 |
| Number of pages | 3 |
| Journal | SIGIR Forum (ACM Special Interest Group on Information Retrieval) |
| State | Published - 2000 |
| Externally published | Yes |
| Event | Proceedings of the 23rd International ACM SIGIR Conference on Research and Development in Infornation Retrieval (SIGIR 2000) - Athens, Greece Duration: 24 Jul 2000 → 28 Jul 2000 |