Search (2 results, page 1 of 1)

  • × author_ss:"Keskustalo, H."
  • × theme_ss:"Multilinguale Probleme"
  1. Lehtokangas, R.; Keskustalo, H.; Järvelin, K.: Experiments with transitive dictionary translation and pseudo-relevance feedback using graded relevance assessments (2008) 0.00
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    Abstract
    In this article, the authors present evaluation results for transitive dictionary-based cross-language information retrieval (CLIR) using graded relevance assessments in a best match retrieval environment. A text database containing newspaper articles and a related set of 35 search topics were used in the tests. Source language topics (in English, German, and Swedish) were automatically translated into the target language (Finnish) via an intermediate (or pivot) language. Effectiveness of the transitively translated queries was compared to that of the directly translated and monolingual Finnish queries. Pseudo-relevance feedback (PRF) was also used to expand the original transitive target queries. Cross-language information retrieval performance was evaluated on three relevance thresholds: stringent, regular, and liberal. The transitive translations performed well achieving, on the average, 85-93% of the direct translation performance, and 66-72% of monolingual performance. Moreover, PRF was successful in raising the performance of transitive translation routes in absolute terms as well as in relation to monolingual and direct translation performance applying PRF.
    Source
    Journal of the American Society for Information Science and Technology. 59(2008) no.3, S.476-488
  2. Toivonen, J.; Pirkola, A.; Keskustalo, H.; Visala, K.; Järvelin, K.: Translating cross-lingual spelling variants using transformation rules (2005) 0.00
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    Abstract
    Technical terms and proper names constitute a major problem in dictionary-based cross-language information retrieval (CLIR). However, technical terms and proper names in different languages often share the same Latin or Greek origin, being thus spelling variants of each other. In this paper we present a novel two-step fuzzy translation technique for cross-lingual spelling variants. In the first step, transformation rules are applied to source words to render them more similar to their target language equivalents. The rules are generated automatically using translation dictionaries as source data. In the second step, the intermediate forms obtained in the first step are translated into a target language using fuzzy matching. The effectiveness of the technique was evaluated empirically using five source languages and English as a target language. The two-step technique performed better, in some cases considerably better, than fuzzy matching alone. Even using the first step as such showed promising results.
    Source
    Information processing and management. 41(2005) no.4, S.859-872