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Chinese query correction based on the combination of statistics and characteristics

机译:基于统计和特征的组合的中文查询校正

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In the Retrieval System, the query words correction is an important auxiliary in improving query efficiency. In this paper, according to the characteristics of the Chinese language, a candidate set has been generated for each term of the query string. After the cross combination of the candidate sets, the grid of candidates is created. With the characteristic form combining the factor of n-gram statistical model and phonetic similarity, query term hits, and n-gram similarity, the candidates ranking model has been set and generally balanced, then the candidates are sorted to get the optimal correction results. The experiments show that, our query correction model based on the combination of statistics and characteristics has obtained higher correction accuracy and recall rate.
机译:在检索系统中,查询单词校正是提高查询效率的重要辅助。本文根据中文的特征,已经为查询字符串的每个术语生成了候选集。在候选集的跨组合之后,创建候选者网格。利用组合N-GRAM统计模型和语音相似度的因子的特征形式,查询术语命中和N-GRAM相似性,已经设定并通常平衡候选排名模型,然后对候选进行分类以获得最佳校正结果。实验表明,我们的查询校正模型基于统计和特性的组合已经获得了更高的校正精度和召回速率。

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