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https://issues.apache.org/jira/browse/OPENNLP-757?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14362333#comment-14362333
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Rohit Shinde commented on OPENNLP-757:
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Hello all,
I am Rohit Shinde and I have been using NLP techniques for my major project.
The major part of the NLP that we used was POS tagging and dependency parsing.
We had used Stanford's CoreNLP package.
I am fairly proficient in Python, Java and C++. I have a good understanding of
Machine Learning algorithms as well as Data Mining algorithms.
I would like to contribute to OpenNLP and I would like to work on implementing
this feature. How would I go about doing this?
Thanks.
Rohit Shinde
> 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
> Labels: gsoc, gsoc2015, java, nlp, wsd
>
> 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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