Theme: A Study of Classifier Combination and Semi-Supervised Learning for Word Sense Disambiguation
نویسنده
چکیده
1. Aims Word Sense Disambiguation (WSD) involves the association of a polysemous word in a text or discourse with a particular sense among numerous potential senses of that word. In my thesis, we present a study of classifier combination and semi-supervised learning for WSD, which aim to boost supervised WSD and improve accuracy of WSD. In addition, we also work on context representation and feature selection which play important roles in obtaining high accuracy of WSD task.
منابع مشابه
Semi-supervised learning integrated with classifier combination for word sense disambiguation
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تاریخ انتشار 2007