Retrieval Experiments at Morpho Challenge 2008
Paul McNamee · CLEF (Working Notes) · 2008
Morpho Challenge 2008 hosted an extrinsic evaluation of morphological analysis that explored whether unsupervised morphology induction could benet information retrieval. This paper presents results in alternative methods for word normalization using test sets from the Cross-Language Evaluation Forum (CLEF) ad-hoc collections. Preliminary results for the Morpho Challenge 2008 evaluation are consistent with these data. We found that: (1) rule-based stemming is eective in less morphologically complicated languages; (2) alternative methods for stemming such as unsupervised learning of morphemes and least common n-gram stemming are helpful; and, (3) full character n-gram indexing is the most eective form of tokenization in more morphologically complex languages.