An Empirical Study of Classifier Combination Based Word Sense Disambiguation
نویسندگان
چکیده
منابع مشابه
An Empirical Study on Class-Based Word Sense Disambiguation
As empirically demonstrated by the last SensEval exercises, assigning the appropriate meaning to words in context has resisted all attempts to be successfully addressed. One possible reason could be the use of inappropriate set of meanings. In fact, WordNet has been used as a de-facto standard repository of meanings. However, to our knowledge, the meanings represented by WordNet have been only ...
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This paper demonstrates the substantial empirical success of classifier combination for the word sense disambiguation task. It investigates more than 10 classifier combination methods, including second order classifier stacking, over 6 major structurally different base classifiers (enhanced Naïve Bayes, cosine, Bayes Ratio, decision lists, transformationbased learning and maximum variance boost...
متن کاملExploiting Parallel Texts for Word Sense Disambiguation: An Empirical Study
A central problem of word sense disambiguation (WSD) is the lack of manually sense-tagged data required for supervised learning. In this paper, we evaluate an approach to automatically acquire sensetagged training data from English-Chinese parallel corpora, which are then used for disambiguating the nouns in the SENSEVAL-2 English lexical sample task. Our investigation reveals that this method ...
متن کاملWord Sense Disambiguation Using OntoNotes: An Empirical Study
The accuracy of current word sense disambiguation (WSD) systems is affected by the fine-grained sense inventory of WordNet as well as a lack of training examples. Using the WSD examples provided through OntoNotes, we conduct the first large-scale WSD evaluation involving hundreds of word types and tens of thousands of sense-tagged examples, while adopting a coarse-grained sense inventory. We sh...
متن کاملTheme: A Study of Classifier Combination and Semi-Supervised Learning for Word Sense Disambiguation
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 fe...
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ژورنال
عنوان ژورنال: IEICE Transactions on Information and Systems
سال: 2018
ISSN: 0916-8532,1745-1361
DOI: 10.1587/transinf.2017edp7090