An Application of Latent Semantic Analysis to Word Sense Discrimination for Words with Related and Unrelated Meanings
نویسندگان
چکیده
We present an application of Latent Semantic Analysis to word sense discrimination within a tutor for English vocabulary learning. We attempt to match the meaning of a word in a document with the meaning of the same word in a fill-in-the-blank question. We compare the performance of the Lesk algorithm to Latent Semantic Analysis. We also compare the performance of Latent Semantic Analysis on a set of words with several unrelated meanings and on a set of words having both related and unrelated meanings.
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تاریخ انتشار 2009