Experimental Analysis of Stemming on Jurisprudential Documents Retrieval†
AbstractStemming algorithms are commonly used during textual preprocessing phase in order to reduce data dimensionality. However, this reduction presents different efficacy levels depending on the domain that it is applied to. Thus, for instance, there are reports in the literature that show the effect of stemming when applied to dictionaries or textual bases of news. On the other hand, we have not found any studies analyzing the impact of radicalization on Brazilian judicial jurisprudence, composed of decisions handed down by the judiciary, a fundamental instrument for law professionals to play their role. Thus, this work presents two complete experiments, showing the results obtained through the analysis and evaluation of the stemmers applied on real jurisprudential documents, originating from the Court of Justice of the State of Sergipe. In the first experiment, the results showed that, among the analyzed algorithms, the RSLP (Removedor de Sufixos da Lingua Portuguesa) possessed the greatest capacity of dimensionality reduction of the data. In the second one, through the evaluation of the stemming algorithms on the legal documents retrieval, the RSLP-S (Removedor de Sufixos da Lingua Portuguesa Singular) and UniNE (University of Neuchâtel), less aggressive stemmers, presented the best cost-benefit ratio, since they reduced the dimensionality of the data and increased the effectiveness of the information retrieval evaluation metrics in one of analyzed collections. View Full-Text
Share & Cite This Article
N. de Oliveira, R.A.; C. Junior, M. Experimental Analysis of Stemming on Jurisprudential Documents Retrieval. Information 2018, 9, 28.
N. de Oliveira RA, C. Junior M. Experimental Analysis of Stemming on Jurisprudential Documents Retrieval. Information. 2018; 9(2):28.Chicago/Turabian Style
N. de Oliveira, Robert A.; C. Junior, Methanias. 2018. "Experimental Analysis of Stemming on Jurisprudential Documents Retrieval." Information 9, no. 2: 28.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.