Comparing measures of semantic similarity (CROSBI ID 571694)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Ljubešić, Nikola ; Boras, Damir ; Bakarić, Nikola ; Njavro, Jasmina
engleski
Comparing measures of semantic similarity
The aim of this paper is to compare different methods for automatic extraction of semantic similarity measures from corpora. The semantic similarity measure is proven to be very useful for many tasks in natural language processing like information retrieval, information extraction, machine translation etc. Additionally, one of the main problems in natural language processing is data sparseness since no language sample is large enough to seize all possible language combinations. In our research we experiment with four different measures of association with context and eight different measures of vector similarity. The results show that the Jensen-Shannon divergence and L1 and L2 norm outperform other measures of vector similarity regardless of the measure of association with context used. Maximum likelihood estimate and t-test show better results than other measures of association with context.
calculating semantic similarity ; context ; association measures ; similarity measures
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Podaci o prilogu
675-682.
2008.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 30th International Conference on Information Technology Interfaces
Hljuz Dobrić, Vesna
Institute of Electrical and Electronics Engineers (IEEE)
978-953-7138-12-7
1330-1012
Podaci o skupu
30th International Conference on Information Technology Interfaces
predavanje
23.06.2008-26.06.2008
Dubrovnik, Hrvatska