Search (3 results, page 1 of 1)

  • × author_ss:"Järvelin, K."
  • × author_ss:"Keskustalo, H."
  • × author_ss:"Pirkola, A."
  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. Ferro, N.; Silvello, G.; Keskustalo, H.; Pirkola, A.; Järvelin, K.: ¬The twist measure for IR evaluation : taking user's effort into account (2016) 0.00 
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    Abstract
    We present a novel measure for ranking evaluation, called Twist (t). It is a measure for informational intents, which handles both binary and graded relevance. t stems from the observation that searching is currently a that searching is currently taken for granted and it is natural for users to assume that search engines are available and work well. As a consequence, users may assume the utility they have in finding relevant documents, which is the focus of traditional measures, as granted. On the contrary, they may feel uneasy when the system returns nonrelevant documents because they are then forced to do additional work to get the desired information, and this causes avoidable effort. The latter is the focus of t, which evaluates the effectiveness of a system from the point of view of the effort required to the users to retrieve the desired information. We provide a formal definition of t, a demonstration of its properties, and introduce the notion of effort/gain plots, which complement traditional utility-based measures. By means of an extensive experimental evaluation, t is shown to grasp different aspects of system performances, to not require extensive and costly assessments, and to be a robust tool for detecting differences between systems.
    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

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