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To stem or lemmatize a highly inflectional language in a probabilistic IR environment?

Kimmo Kettunen (Department of Information Studies, University of Tampere, Tampere, Finland)
Tuomas Kunttu (Department of Information Studies, University of Tampere, Tampere, Finland)
Kalervo Järvelin (Department of Information Studies, University of Tampere, Tampere, Finland)

Journal of Documentation

ISSN: 0022-0418

Article publication date: 1 August 2005

917

Abstract

Purpose

To show that stem generation compares well with lemmatization as a morphological tool for a highly inflectional language for IR purposes in a best‐match retrieval system.

Design/methodology/approach

Effects of three different morphological methods – lemmatization, stemming and stem production – for Finnish are compared in a probabilistic IR environment (INQUERY). Evaluation is done using a four‐point relevance scale which is partitioned differently in different test settings.

Findings

Results show that stem production, a lighter method than morphological lemmatization, compares well with lemmatization in a best‐match IR environment. Differences in performance between stem production and lemmatization are small and they are not statistically significant in most of the tested settings. It is also shown that hitherto a rather neglected method of morphological processing for Finnish, stemming, performs reasonably well although the stemmer used – a Porter stemmer implementation – is far from optimal for a morphologically complex language like Finnish. In another series of tests, the effects of compound splitting and derivational expansion of queries are tested.

Practical implications

Usefulness of morphological lemmatization and stem generation for IR purposes can be estimated with many factors. On the average P‐R level they seem to behave very close to each other in a probabilistic IR system. Thus, the choice of the used method with highly inflectional languages needs to be estimated along other dimensions too.

Originality/value

Results are achieved using Finnish as an example of a highly inflectional language. The results are of interest for anyone who is interested in processing of morphological variation of a highly inflected language for IR purposes.

Keywords

Citation

Kettunen, K., Kunttu, T. and Järvelin, K. (2005), "To stem or lemmatize a highly inflectional language in a probabilistic IR environment?", Journal of Documentation, Vol. 61 No. 4, pp. 476-496. https://doi.org/10.1108/00220410510607480

Publisher

:

Emerald Group Publishing Limited

Copyright © 2005, Emerald Group Publishing Limited

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