Term extraction using machine learning
نویسنده
چکیده
In this term paper I motivate and describe a monolingual term extraction method using the Ripper machine learning algorithm and linguistic and statistical features of n-grams extracted from a patent text corpus. The n-grams are labeled as terms or non-terms using a manually validated term list based on the same patent text corpus. The results for experiments conducted show promise for further research as the method allows for evaluation of termness metrics and provides data for theoretical analysis on termness.
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