Abstract. We aim in this research to find and compare cross-lingual articles concerning a specific topic. So, we need a measure to compare articles. This measure can be based on bilingual dictionary or based on numerical methods such as Latent Semantic Indexing (LSI). In this paper, we use LSI in two ways to retrieve Arabic-English comparable articles. The first one is monolingual: the English article is translated into Arabic and then mapped into the LSI Arabic space; the second one is cross-lingual: Arabic and English documents are mapped into LSI Arabic-English space. Then, we compare LSI approaches to the dictionary-based approach on several English-Arabic parallel and comparable corpora. Results indicate that the performance of cross-lingual LSI approach is competitive to monolingual approach, or even better for some corpora. Moreover both LSI approaches outperform dictionary approach.
Very similarly to the work presented in this paper, REF use LSI for identification of parallel and comparable corpora.
Cross-Lingual Semantic Similarity Measure for Comparable Articles
PolTAL
Computer Science