A neural network for probabilistic information retrieval
- 1 May 1989
- journal article
- Published by Association for Computing Machinery (ACM) in ACM SIGIR Forum
- Vol. 23 (SI) , 21-30
- https://doi.org/10.1145/75335.75338
Abstract
This paper demonstrates how a neural network may be constructed, together with learning algorithms and modes of operation, that will provide retrieval effectiveness similar to that of the probabilistic indexing and retrieval model based on single terms as document components.Keywords
This publication has 22 references indexed in Scilit:
- Experiments with document components for indexing and retrievalInformation Processing & Management, 1988
- On modeling of information retrieval concepts in vector spacesACM Transactions on Database Systems, 1987
- Learning representations by back-propagating errorsNature, 1986
- A probabilistic theory of indexing and similarity measure based on cited and citing documentsJournal of the American Society for Information Science, 1985
- Extended Boolean information retrievalCommunications of the ACM, 1983
- Toward a modern theory of adaptive networks: Expectation and prediction.Psychological Review, 1981
- A THEORETICAL BASIS FOR THE USE OF CO‐OCCURRENCE DATA IN INFORMATION RETRIEVALJournal of Documentation, 1977
- Precision Weighting—An Effective Automatic Indexing MethodJournal of the ACM, 1976
- The Cortex of the CerebellumScientific American, 1975
- A STATISTICAL INTERPRETATION OF TERM SPECIFICITY AND ITS APPLICATION IN RETRIEVALJournal of Documentation, 1972