Word Sense Disambiguation using Aggregated Similarity based on WordNet Graph Representation
The term of word sense disambiguation, WSD, is introduced in the context of text document processing. A knowledge based approach is conducted using WordNet lexical ontology, describing its structure and components used for the process of identification of context related senses of each polysemy word...
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doaj-744eb538bfb44394bab171058fddd80d2020-11-24T23:13:44ZengInforec AssociationInformatică economică1453-13051842-80882013-01-0117316918010.12948/issn14531305/17.3.2013.15Word Sense Disambiguation using Aggregated Similarity based on WordNet Graph RepresentationMădălina ZURINIThe term of word sense disambiguation, WSD, is introduced in the context of text document processing. A knowledge based approach is conducted using WordNet lexical ontology, describing its structure and components used for the process of identification of context related senses of each polysemy words. The principal distance measures using the graph associated to WordNet are presented, analyzing their advantages and disadvantages. A general model for aggregation of distances and probabilities is proposed and implemented in an application in order to detect the context senses of each word. For the non-existing words from WordNet, a similarity measure is used based on probabilities of co-occurrences. The module of WSD is proposed for integration in the step of processing documents such as supervised and unsupervised classification in order to maximize the correctness of the classification. Future work is related to the implementation of different domain oriented ontologies.http://revistaie.ase.ro/content/67/15%20-%20Zurini.pdfWSDSimilarity MeasureWordNetOntologySynset |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mădălina ZURINI |
spellingShingle |
Mădălina ZURINI Word Sense Disambiguation using Aggregated Similarity based on WordNet Graph Representation Informatică economică WSD Similarity Measure WordNet Ontology Synset |
author_facet |
Mădălina ZURINI |
author_sort |
Mădălina ZURINI |
title |
Word Sense Disambiguation using Aggregated Similarity based on WordNet Graph Representation |
title_short |
Word Sense Disambiguation using Aggregated Similarity based on WordNet Graph Representation |
title_full |
Word Sense Disambiguation using Aggregated Similarity based on WordNet Graph Representation |
title_fullStr |
Word Sense Disambiguation using Aggregated Similarity based on WordNet Graph Representation |
title_full_unstemmed |
Word Sense Disambiguation using Aggregated Similarity based on WordNet Graph Representation |
title_sort |
word sense disambiguation using aggregated similarity based on wordnet graph representation |
publisher |
Inforec Association |
series |
Informatică economică |
issn |
1453-1305 1842-8088 |
publishDate |
2013-01-01 |
description |
The term of word sense disambiguation, WSD, is introduced in the context of text document processing. A knowledge based approach is conducted using WordNet lexical ontology, describing its structure and components used for the process of identification of context related senses of each polysemy words. The principal distance measures using the graph associated to WordNet are presented, analyzing their advantages and disadvantages. A general model for aggregation of distances and probabilities is proposed and implemented in an application in order to detect the context senses of each word. For the non-existing words from WordNet, a similarity measure is used based on probabilities of co-occurrences. The module of WSD is proposed for integration in the step of processing documents such as supervised and unsupervised classification in order to maximize the correctness of the classification. Future work is related to the implementation of different domain oriented ontologies. |
topic |
WSD Similarity Measure WordNet Ontology Synset |
url |
http://revistaie.ase.ro/content/67/15%20-%20Zurini.pdf |
work_keys_str_mv |
AT madalinazurini wordsensedisambiguationusingaggregatedsimilaritybasedonwordnetgraphrepresentation |
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1725596772098637824 |