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A Text Mining-Based Approach for Analyzing Information Retrieval in Spanish: Music Data Collection as a Case Study

  • Juan Ramos-GonzálezEmail author
  • Lucía Martín-Gómez
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 801)

Abstract

This paper presents a text mining-based search approach aimed at information retrieval in the Spanish language. For this purpose, a tool has been developed in order to facilitate and automate the analysis and retrieval, allowing the user to apply different analyzers when carrying out a query, to index and delete documents stored in the system and to evaluate the recovery process. To this extent, a dataset consisting in 27 songs has been used as a case study. Different queries have been made to investigate about the best fitting approaches to the Spanish language and their suitability depending on the query text.

Keywords

Text mining Information retrieval Stemming Spanish 

Notes

Acknowledgments

This work has been supported by project MOVIURBAN Máquina social para la gestión sostenible de ciudades inteligentes: movilidad urbana, datos abiertos, sensores móviles (SA070U 16). Project cofinanced with Junta Castilla y Leon, Consejera de Educacion and FEDER funds. In addition, the research of Juan Ramos González has been co-financed by the European Social Fund and Junta de Castilla y León (Operational Programme 2014-2020 for Castilla y León, BOCYL EDU/602/2016).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.BISITE Digital Innovation HubUniversity of Salamanca, Edificio Multiusos I+D+iSalamancaSpain

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