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

  • Angel Sancho Ferrer
  • Jose Manuel Mateo Rivero
  • Alejandro Mesas García
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4884)


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.


Legal Knowledge Representation Information Retrieval Semantic Indexation Hybrid Methodologies Genetic Algorithms Machine Learning 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Angel Sancho Ferrer
    • 1
  • Jose Manuel Mateo Rivero
    • 1
  • Alejandro Mesas García
    • 1
  1. 1.Research & Development DepartmentWolters Kluwer SpainMadridSpain

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