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ALIGNMENT OF CUSTOM STANDARDS BY MACHINE LEARNING ALGORITHMS.
- Source :
- Studia Universitatis Babes-Bolyai, Informatica; 2010, Vol. 55 Issue 1, p25-36, 12p, 1 Chart
- Publication Year :
- 2010
-
Abstract
- Building an efficient model for automatic alignment of terminologies would bring a significant improvement to the information retrieval process. We have developed and compared two machine learning based algorithms whose aim is to align 2 custom standards built on a 3 level taxonomy, using kNN and SVM classifiers that work on a vector representation consisting of several similarity measures. The weights utilized by the kNN were optimized with an evolutionary algorithm, while the SVM classifier's hyper-parameters were optimized with a grid search algorithm. The database used for train was semi automatically obtained by using the Coma++ tool. The performance of our aligners is shown by the results obtained on the test set. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1224869X
- Volume :
- 55
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Studia Universitatis Babes-Bolyai, Informatica
- Publication Type :
- Academic Journal
- Accession number :
- 54425552