Cross-lingual word similarity (CLWS) is a basic component in cross-lingual information access systems. Designing a CLWS measure faces three challenges: (i) Cross-lingual knowledge base is rare; (ii) Cross-lingual corpora are limited; and (iii) No benchmark cross-lingual dataset is available for CLWS evaluation. This paper presents some Chinese-English CLWS measures that adopt HowNet as cross-lingual knowledge base and sentence-level parallel corpus as development data. In order to evaluate these measures, a Chinese-English cross-lingual benchmark dataset is compiled based on the Miller-Charles' dataset. Two conclusions are drawn from the experimental results. Firstly, HowNet is a promising knowledge base for the CLWS measure. Secondly, parallel corpus is promising to fine-tune the word similarity measures using cross-lingual co-occurrence statistics. © 2011 Springer-Verlag.
CITATION STYLE
Xia, Y., Zhao, T., Yao, J., & Jin, P. (2011). Measuring Chinese-English cross-lingual word similarity with HowNet and parallel corpus. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6609 LNCS, pp. 221–233). https://doi.org/10.1007/978-3-642-19437-5_18
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