Levenshtein distance for information extraction in databases and for natural language processing.

Detalhes bibliográficos
Ano de defesa: 2007
Autor(a) principal: Bruno Woltzenlogel Paleo
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Instituto Tecnológico de Aeronáutica
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Processamento de textos
Linguagem natural (computadores)
Rotinas de edição (computadores)
Teoria da informação
Computação
Link de acesso: http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=529
Resumo: While performing information extraction or natural language processing tasks, one usually encounters problems when working with data or texts containing noise, typing mistakes or other different kinds of errors. In this thesis we investigate the use of modified Levenshtein edit distances to deal with these problems in two specific tasks. The first one is the record linkage in databases where distinct records can be representing the same entity. For this task we used and extended the WEKA API for Machine Learning and we were able to show that a modified Levenshtein distance provides good precision and recall results in the detection of records representing the same entities. The second task is the search and annotation of occurrences of specified words in texts written in natural language. Our main result in this task was the implementation of an approximate Gazetteer for GATE, the General Architecture for Text Engineering.
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network_name_str Biblioteca Digital de Teses e Dissertações do ITA
spelling Levenshtein distance for information extraction in databases and for natural language processing.Processamento de textosLinguagem natural (computadores)Rotinas de edição (computadores)Teoria da informaçãoComputaçãoWhile performing information extraction or natural language processing tasks, one usually encounters problems when working with data or texts containing noise, typing mistakes or other different kinds of errors. In this thesis we investigate the use of modified Levenshtein edit distances to deal with these problems in two specific tasks. The first one is the record linkage in databases where distinct records can be representing the same entity. For this task we used and extended the WEKA API for Machine Learning and we were able to show that a modified Levenshtein distance provides good precision and recall results in the detection of records representing the same entities. The second task is the search and annotation of occurrences of specified words in texts written in natural language. Our main result in this task was the implementation of an approximate Gazetteer for GATE, the General Architecture for Text Engineering.Instituto Tecnológico de AeronáuticaCarlos Henrique Costa RibeiroBruno Woltzenlogel Paleo2007-12-21info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=529reponame:Biblioteca Digital de Teses e Dissertações do ITAinstname:Instituto Tecnológico de Aeronáuticainstacron:ITAenginfo:eu-repo/semantics/openAccessapplication/pdf2019-02-02T14:01:50Zoai:agregador.ibict.br.BDTD_ITA:oai:ita.br:529http://oai.bdtd.ibict.br/requestopendoar:null2020-05-28 19:33:31.167Biblioteca Digital de Teses e Dissertações do ITA - Instituto Tecnológico de Aeronáuticatrue
dc.title.none.fl_str_mv Levenshtein distance for information extraction in databases and for natural language processing.
title Levenshtein distance for information extraction in databases and for natural language processing.
spellingShingle Levenshtein distance for information extraction in databases and for natural language processing.
Bruno Woltzenlogel Paleo
Processamento de textos
Linguagem natural (computadores)
Rotinas de edição (computadores)
Teoria da informação
Computação
title_short Levenshtein distance for information extraction in databases and for natural language processing.
title_full Levenshtein distance for information extraction in databases and for natural language processing.
title_fullStr Levenshtein distance for information extraction in databases and for natural language processing.
title_full_unstemmed Levenshtein distance for information extraction in databases and for natural language processing.
title_sort Levenshtein distance for information extraction in databases and for natural language processing.
author Bruno Woltzenlogel Paleo
author_facet Bruno Woltzenlogel Paleo
author_role author
dc.contributor.none.fl_str_mv Carlos Henrique Costa Ribeiro
dc.contributor.author.fl_str_mv Bruno Woltzenlogel Paleo
dc.subject.por.fl_str_mv Processamento de textos
Linguagem natural (computadores)
Rotinas de edição (computadores)
Teoria da informação
Computação
topic Processamento de textos
Linguagem natural (computadores)
Rotinas de edição (computadores)
Teoria da informação
Computação
dc.description.none.fl_txt_mv While performing information extraction or natural language processing tasks, one usually encounters problems when working with data or texts containing noise, typing mistakes or other different kinds of errors. In this thesis we investigate the use of modified Levenshtein edit distances to deal with these problems in two specific tasks. The first one is the record linkage in databases where distinct records can be representing the same entity. For this task we used and extended the WEKA API for Machine Learning and we were able to show that a modified Levenshtein distance provides good precision and recall results in the detection of records representing the same entities. The second task is the search and annotation of occurrences of specified words in texts written in natural language. Our main result in this task was the implementation of an approximate Gazetteer for GATE, the General Architecture for Text Engineering.
description While performing information extraction or natural language processing tasks, one usually encounters problems when working with data or texts containing noise, typing mistakes or other different kinds of errors. In this thesis we investigate the use of modified Levenshtein edit distances to deal with these problems in two specific tasks. The first one is the record linkage in databases where distinct records can be representing the same entity. For this task we used and extended the WEKA API for Machine Learning and we were able to show that a modified Levenshtein distance provides good precision and recall results in the detection of records representing the same entities. The second task is the search and annotation of occurrences of specified words in texts written in natural language. Our main result in this task was the implementation of an approximate Gazetteer for GATE, the General Architecture for Text Engineering.
publishDate 2007
dc.date.none.fl_str_mv 2007-12-21
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/masterThesis
status_str publishedVersion
format masterThesis
dc.identifier.uri.fl_str_mv http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=529
url http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=529
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Instituto Tecnológico de Aeronáutica
publisher.none.fl_str_mv Instituto Tecnológico de Aeronáutica
dc.source.none.fl_str_mv reponame:Biblioteca Digital de Teses e Dissertações do ITA
instname:Instituto Tecnológico de Aeronáutica
instacron:ITA
reponame_str Biblioteca Digital de Teses e Dissertações do ITA
collection Biblioteca Digital de Teses e Dissertações do ITA
instname_str Instituto Tecnológico de Aeronáutica
instacron_str ITA
institution ITA
repository.name.fl_str_mv Biblioteca Digital de Teses e Dissertações do ITA - Instituto Tecnológico de Aeronáutica
repository.mail.fl_str_mv
subject_por_txtF_mv Processamento de textos
Linguagem natural (computadores)
Rotinas de edição (computadores)
Teoria da informação
Computação
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