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

Effects of three different morphological methods-lemmatization, stemming and inflectional stem generation-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. Results show that inflectional stem generation which has not been used much in IR, compares well with lemmatization in a best-match IR environment. Differences in performance between inflectional stem generation 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 2 compound splitting and derivational expansion of queries are tested.