Master Dissertation : Information Retrieval for Question Answering based on Distributed Representations

Commonly used methods for information retrieval such as TFIDF do not capture the semantics of the query or the document. This is a problem, especially in cases where the words used in the queries are not contained in the documents. Therefore more research needs to be done to investigate how text sem...

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Detalles Bibliográficos
Autor: Sagrado Sala, Ana
Tipo de recurso: tesis de maestría
Fecha de publicación:2022
País:España
Institución:Universidad Nacional de Educación a Distancia
Repositorio:e-spacio. Repositorio Institucional de la UNED
Idioma:inglés
OAI Identifier:oai:e-spacio.uned.es:20.500.14468/14297
Acceso en línea:https://hdl.handle.net/20.500.14468/14297
Access Level:acceso abierto
Palabra clave:1203 Ciencia de los ordenadores
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spelling Master Dissertation : Information Retrieval for Question Answering based on Distributed RepresentationsSagrado Sala, Ana1203 Ciencia de los ordenadoresCommonly used methods for information retrieval such as TFIDF do not capture the semantics of the query or the document. This is a problem, especially in cases where the words used in the queries are not contained in the documents. Therefore more research needs to be done to investigate how text semantics can be applied to information retrieval, especially in cases where the corpus of documents is big and the queries and documents representations need to be compared fast and without the need of re-indexing. In this work, we conduct an exploratory study to investigate different embeddings and deep learning techniques and how this can be applied to the information retrieval task. We show that although existing methods based on word overlapping perform better in general, in particular cases where the word overlap between queries and documents is low, the use of semantic embedding outperforms other methods based on bag of words.Universidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Lenguajes y Sistemas InformáticosLópez Ostenero, FernandoRodrigo Yuste, Álvaroe-Spacio UNED20242024-05-2020222022-02-0120222022-02-01master thesishttp://purl.org/coar/resource_type/c_bdccinfo:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/20.500.14468/14297reponame:e-spacio. Repositorio Institucional de la UNEDinstname:Universidad Nacional de Educación a DistanciaInglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.esoai:e-spacio.uned.es:20.500.14468/142972026-06-06T12:38:31Z
dc.title.none.fl_str_mv Master Dissertation : Information Retrieval for Question Answering based on Distributed Representations
title Master Dissertation : Information Retrieval for Question Answering based on Distributed Representations
spellingShingle Master Dissertation : Information Retrieval for Question Answering based on Distributed Representations
Sagrado Sala, Ana
1203 Ciencia de los ordenadores
title_short Master Dissertation : Information Retrieval for Question Answering based on Distributed Representations
title_full Master Dissertation : Information Retrieval for Question Answering based on Distributed Representations
title_fullStr Master Dissertation : Information Retrieval for Question Answering based on Distributed Representations
title_full_unstemmed Master Dissertation : Information Retrieval for Question Answering based on Distributed Representations
title_sort Master Dissertation : Information Retrieval for Question Answering based on Distributed Representations
dc.creator.none.fl_str_mv Sagrado Sala, Ana
author Sagrado Sala, Ana
author_facet Sagrado Sala, Ana
author_role author
dc.contributor.none.fl_str_mv López Ostenero, Fernando
Rodrigo Yuste, Álvaro
e-Spacio UNED
dc.subject.none.fl_str_mv 1203 Ciencia de los ordenadores
topic 1203 Ciencia de los ordenadores
description Commonly used methods for information retrieval such as TFIDF do not capture the semantics of the query or the document. This is a problem, especially in cases where the words used in the queries are not contained in the documents. Therefore more research needs to be done to investigate how text semantics can be applied to information retrieval, especially in cases where the corpus of documents is big and the queries and documents representations need to be compared fast and without the need of re-indexing. In this work, we conduct an exploratory study to investigate different embeddings and deep learning techniques and how this can be applied to the information retrieval task. We show that although existing methods based on word overlapping perform better in general, in particular cases where the word overlap between queries and documents is low, the use of semantic embedding outperforms other methods based on bag of words.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-02-01
2022
2022-02-01
2024
2024-05-20
dc.type.none.fl_str_mv master thesis
http://purl.org/coar/resource_type/c_bdcc
dc.type.openaire.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14468/14297
url https://hdl.handle.net/20.500.14468/14297
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Lenguajes y Sistemas Informáticos
publisher.none.fl_str_mv Universidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Lenguajes y Sistemas Informáticos
dc.source.none.fl_str_mv reponame:e-spacio. Repositorio Institucional de la UNED
instname:Universidad Nacional de Educación a Distancia
instname_str Universidad Nacional de Educación a Distancia
reponame_str e-spacio. Repositorio Institucional de la UNED
collection e-spacio. Repositorio Institucional de la UNED
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.81155

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