[jira] [Created] (OPENNLP-757) Supervised WSD techniques

["Mondher Bouazizi (JIRA)" <ji...@apache.org>]

Mondher Bouazizi created OPENNLP-757:
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             Summary: Supervised WSD techniques
                 Key: OPENNLP-757
                 URL: https://issues.apache.org/jira/browse/OPENNLP-757
             Project: OpenNLP
          Issue Type: New Feature
          Components: Machine Learning, POS Tagger, Sentence Detector, Stemmer
            Reporter: Mondher Bouazizi


The objective of Word Sense Disambiguation (WSD) is to determine which sense of a word is meant in a particular context. Therefore, WSD is a classification task, where the classes are the different senses of the ambiguous word.
Different techniques are proposed in the academic literature, which fall mainly into two categories: Supervised and Unsupervised.
For this component, we focus on supervised techniques: these approaches use machine-learning techniques to learn a classifier from labeled training sets.
The object of this project is to create a WSD solution (for English) that implements some supervised techniques. For example:
        Decision Lists
        Decision Trees
        Naive Bayes
        Neural Networks
        Exemplar-Based or Instance-Based Learning
        Support Vector Machines
        Ensemble Methods
        Semi-supervised Disambiguation
        Etc.



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