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Translation Probabilities in Cross-Language Information Retrieval

机译：跨语言信息检索中的翻译概率

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摘要

Translation ambiguity is a major problem in dictionary-based cross-language information retrieval. To attack the problem, indirect disambiguation approaches, which do not explicitly resolve translation ambiguity, rely on query-structuring techniques such as a structured Boolean model and Pirkola's method. Direct disambiguation approaches try to assign translation probabilities to translation equivalents, normally by employing co-occurrence statistics of target language terms from target documents as disambiguation clues. Thus far, translation probabilities have not been well explored in terms of statistical query translation models, query formulation, or cross-lingual retrieval models, etc. In order to study the impact of translation probabilities on retrieval effectiveness in direct disambiguation approaches, this paper empirically investigates the following issues: different disambiguation factors affecting the calculation of translation probabilities, the comparison of cross-lingual query formulation techniques involving translation probabilities, the relationship between the accuracy of translation disambiguation and retrieval effectiveness, and the relationship between top n translations and retrieval effectiveness.
机译：在基于字典的跨语言信息检索中，翻译歧义是一个主要问题。为了解决这个问题，间接消除歧义的方法不能明确解决翻译的歧义，而是依靠查询结构化技术，例如结构化布尔模型和Pirkola方法。直接消歧方法通常通过将目标文档中目标语言术语的共现统计用作消歧线索，来尝试将翻译概率分配给翻译对等物。到目前为止，还没有从统计查询翻译模型，查询表述或跨语言检索模型等方面很好地研究翻译概率。为了研究直接歧义化方法中翻译概率对检索效率的影响，本文进行了实证研究研究以下问题：影响翻译概率计算的歧义消除因素；涉及翻译概率的跨语言查询表述技术的比较；翻译歧义消除的准确性与检索效率之间的关系；排名前n的翻译与检索有效性之间的关系。

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