Search (4 results, page 1 of 1)

  • × author_ss:"Järvelin, K."
  • × author_ss:"Pirkola, A."
  • × year_i:[2000 TO 2010}
  1. Pirkola, A.; Hedlund, T.; Keskustalo, H.; Järvelin, K.: Dictionary-based cross-language information retrieval : problems, methods, and research findings (2001) 0.00 
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    Type
    a
  2. Pirkola, A.; Järvelin, K.: Employing the resolution power of search keys (2001) 0.00 
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    Abstract
    Search key resolution power is analyzed in the context of a request, i.e., among the set of search keys for the request. Methods of characterizing the resolution power of keys automatically are studied, and the effects search keys of varying resolution power have on retrieval effectiveness are analyzed. It is shown that it often is possible to identify the best key of a query while the discrimination between the remaining keys presents problems. It is also shown that query performance is improved by suitably using the best key in a structured query. The tests were run with InQuery in a subcollection of the TREC collection, which contained some 515,000 documents
    Type
    a
  3. 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.
    Type
    a
  4. Pirkola, A.; Puolamäki, D.; Järvelin, K.: Applying query structuring in cross-language retrieval (2003) 0.00 
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    Abstract
    We will explore various ways to apply query structuring in cross-language information retrieval. In the first test, English queries were translated into Finnish using an electronic dictionary, and were run in a Finnish newspaper database of 55,000 articles. Queries were structured by combining the Finnish translation equivalents of the same English query key using the syn-operator of the InQuery retrieval system. Structured queries performed markedly better than unstructured queries. Second, the effects of compound-based structuring using a proximity operator for the translation equivalents of query language compound components were tested. The method was not useful in syn-based queries but resulted in decrease in retrieval effectiveness. Proper names are often non-identical spelling variants in different languages. This allows n-gram based translation of names not included in a dictionary. In the third test, a query structuring method where the Boolean and-operator was used to assign more weight to keys translated through n-gram matching gave good results.
    Type
    a

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