Document (#27778)

Author

Martínez, F.
Martín, M.T.
Rivas, V.M.
Díaz, M.C.
Ureña, L.A.

Title

Using neural networks for multiword recognition in IR

Source

Challenges in knowledge representation and organization for the 21st century: Integration of knowledge across boundaries. Proceedings of the 7th ISKO International Conference Granada, Spain, July 10-13, 2002. Ed.: M. López-Huertas

Imprint

Würzburg : Ergon Verlag

Year

2003

Pages

S.559-564

Series

Advances in knowledge organization; vol.8

Abstract

In this paper, a supervised neural network has been used to classify pairs of terms as being multiwords or non-multiwords. Classification is based an the values yielded by different estimators, currently available in literature, used as inputs for the neural network. Lists of multiwords and non-multiwords have been built to train the net. Afterward, many other pairs of terms have been classified using the trained net. Results obtained in this classification have been used to perform information retrieval tasks. Experiments show that detecting multiwords results in better performance of the IR methods.

Theme

Computerlinguistik

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4. Billal, B.; Fonseca, A.; Sadat, F.; Lounis, H.: Semi-supervised learning and social media text analysis towards multi-labeling categorization (2017) 0.17

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5. Ozmutlu, H.C.; Cavdur, F.; Ozmutlu, S.: Cross-validation of neural network applications for automatic new topic identification (2008) 0.17

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