Hybrid Stemmer for Gujarati
نویسندگان
چکیده
In this paper we present a lightweight stemmer for Gujarati using a hybrid approach. Instead of using a completely unsupervised approach, we have harnessed linguistic knowledge in the form of a hand-crafted Gujarati suffix list in order to improve the quality of the stems and suffixes learnt during the training phase. We used the EMILLE corpus for training and evaluating the stemmer’s performance. The use of hand-crafted suffixes boosted the accuracy of our stemmer by about 17% and helped us achieve an accuracy of 67.86 %.
منابع مشابه
A Lightweight Stemmer for Gujarati
Gujarati is a resource poor language with almost no language processing tools being available. In this paper we have shown an implementation of a rule based stemmer of Gujarati. We have shown the creation of rules for stemming and the richness in morphology that Gujarati possesses. We have also evaluated our results by verifying it with a human expert.
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تاریخ انتشار 2010