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Improvements in Recall and Precision in Wolters Kluwer Spain Legal Search Engine

机译:Wolters Kluwer西班牙法律搜索引擎的召回率和精度提高

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In this paper we describe the search technology in production in Wolters Kluwer Spain for the legal research market. This technology improves the "Google like" experience by increasing both the total number of retrieved documents (recall) and the quality of the very best ones (precision) while maintaining the ease of entering a natural language query. We propose a hybrid approach, both in the working methodology and in the codification of the legal knowledge -subject matter expert and librarian-, through new layers of semantic analysis and algorithms. We improve the traditional tf-idf vector space model by creating a mixed document indexing schema of terms and concepts as well as a proprietary ranking algorithm trained by a hybrid genetic algorithm. These calculations also improve the quality of keyword-in-context.
机译:在本文中,我们描述了法律研究市场在西班牙Wolters Kluwer生产中使用的搜索技术。该技术通过增加检索到的文档的总数(调用)和最佳文档的质量(精确度),同时保持输入自然语言查询的简便性,从而改善了“类似Google的体验”。我们通过语义分析和算法的新层级,在工作方法论和法律知识(主体专家和图书馆员)的编纂中提出了一种混合方法。通过创建术语和概念的混合文档索引架构以及由混合遗传算法训练的专有排名算法,我们改进了传统的tf-idf向量空间模型。这些计算还提高了上下文关键字的质量。

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