Development of Stemming Algorith for Wolaytta Text

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Wolaytta Stemmer

This study describes the design of a stemming algorithm for Wolaytta language.

To give a solid background for the thesis, literatures on conflation in general and stemming algorithms in particular were reviewed.

The result of the study is a prototype context sensitive iterative stemmer for Wolaytta language.

Error counting technique was employed to evaluate the performance of this stemmer.

The stemmer was trained on 3537 words (80% of the sample text) and the improved version reveals an accuracy of 90.6% on the training set.

The number of over stemmed and understemmed words on the training set were 8.6% (304 words) and 0.8% (28 words) respectively.

When the stemmer runs on the unseen sample of 884 words (20% of the sample text), it performed with an accuracy of 86.9%.

The percentage of errors recorded as understemmed and overstemmed on this unseen (test set) were 9% and 4.1%, respectively.

Moreover, a dictionary reduction of 38.92% was attained on the test set.

The major sources of errors are also reported with possible recommendations to further improve the performance of the stemmer and also for further research.

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