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- W2783440180 abstract "Part-of-Speech (POS) tagging is an old and fundamental task in natural language processing. While supervised POS taggers have shown promising accuracy, it is not always feasible to use supervised methods due to lack of labeled data. In this project, we attempt to unsurprisingly induce POS tags by iteratively looking for a recurring pattern of words through a hierarchical agglomerative clustering process. Our approach shows promising results when compared to the tagging results of the state-of-the-art unsupervised POS taggers." @default.
- W2783440180 created "2018-01-26" @default.
- W2783440180 creator A5071488278 @default.
- W2783440180 date "2018-01-10" @default.
- W2783440180 modified "2023-09-27" @default.
- W2783440180 title "Unsupervised Part-of-Speech Induction." @default.
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- W2783440180 hasPublicationYear "2018" @default.
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