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https://issues.apache.org/jira/browse/OPENNLP-758?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Mondher Bouazizi updated OPENNLP-758:
-------------------------------------
Description:
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 unsupervised techniques: these methods are
based on unlabeled data, and do not exploit any manually tagged data.
The object of this project is to create a WSD solution (for English) that
implements some unsupervised techniques. For example:
- Context Clustering
- Word Clustering
- Cooccurrence Graphs
- Overlap of Sense Definitions
- Selectional Preferences
- Structural Approaches
- Etc.
was:
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 unsupervised techniques: these methods are
based on unlabeled data, and do not exploit any manually tagged data.
The object of this project is to create a WSD solution (for English) that
implements some unsupervised techniques. For example:
. Context Clustering
. Word Clustering
. Cooccurrence Graphs
. Overlap of Sense Definitions
. Selectional Preferences
. Structural Approaches
. Etc.
> Unsupervised WSD techniques
> ---------------------------
>
> Key: OPENNLP-758
> URL: https://issues.apache.org/jira/browse/OPENNLP-758
> Project: OpenNLP
> Issue Type: New Feature
> Components: 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 unsupervised techniques: these methods are
> based on unlabeled data, and do not exploit any manually tagged data.
> The object of this project is to create a WSD solution (for English) that
> implements some unsupervised techniques. For example:
> - Context Clustering
> - Word Clustering
> - Cooccurrence Graphs
> - Overlap of Sense Definitions
> - Selectional Preferences
> - Structural Approaches
> - Etc.
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