Proposal of a lightweight, offline, full-text search engine for an mHealth app
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , |
Tipo de documento: | Livro |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/10216/145805 |
Resumo: | - A patient's ability to recall and retrieve health information contributes to a better health management. HealthTalks was developed to address these issues by recording a summary of a medical appointment, uttered by the physician, and transcribing it. For each appointment, the user can also take free-text notes. Nowadays, search engines have become a ubiquitous part of everyone's life and are expected on most applications. Here, we describe the development of a search engine for HealthTalks. The app's characteristics demand a lightweight and offline engine, which requires a specific solution rather than an existing library or service. Our approach combines SQLite's Full-Text Search 4 module, which includes ngram indexing, with traditional information retrieval techniques to rank the documents. We created a test collection with summaries of clinical appointments (our documents), information needs, search queries, and relevance assessments for an initial search engine evaluation. Using this test collection, we assessed performance using NDCG@10, the first rank position of a totally relevant result, and query latency. Results are promising, with an average NDCG of 0.97. The median rank position of the first relevant result varies between 1.9 and 1.95, depending on the use of 4-gram character tokenization, an aspect that did not significantly affect the results. We expect this work to be useful for future developments of full-text search engines in mobile environments. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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Proposal of a lightweight, offline, full-text search engine for an mHealth app- A patient's ability to recall and retrieve health information contributes to a better health management. HealthTalks was developed to address these issues by recording a summary of a medical appointment, uttered by the physician, and transcribing it. For each appointment, the user can also take free-text notes. Nowadays, search engines have become a ubiquitous part of everyone's life and are expected on most applications. Here, we describe the development of a search engine for HealthTalks. The app's characteristics demand a lightweight and offline engine, which requires a specific solution rather than an existing library or service. Our approach combines SQLite's Full-Text Search 4 module, which includes ngram indexing, with traditional information retrieval techniques to rank the documents. We created a test collection with summaries of clinical appointments (our documents), information needs, search queries, and relevance assessments for an initial search engine evaluation. Using this test collection, we assessed performance using NDCG@10, the first rank position of a totally relevant result, and query latency. Results are promising, with an average NDCG of 0.97. The median rank position of the first relevant result varies between 1.9 and 1.95, depending on the use of 4-gram character tokenization, an aspect that did not significantly affect the results. We expect this work to be useful for future developments of full-text search engines in mobile environments.20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/145805eng10.23919/cisti54924.2022.9820062Carla Teixeira LopesAzevedo, DMonteiro, JMinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-08T01:18:37Zoai:repositorio-aberto.up.pt:10216/145805Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:31:51.115736Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Proposal of a lightweight, offline, full-text search engine for an mHealth app |
title |
Proposal of a lightweight, offline, full-text search engine for an mHealth app |
spellingShingle |
Proposal of a lightweight, offline, full-text search engine for an mHealth app Carla Teixeira Lopes |
title_short |
Proposal of a lightweight, offline, full-text search engine for an mHealth app |
title_full |
Proposal of a lightweight, offline, full-text search engine for an mHealth app |
title_fullStr |
Proposal of a lightweight, offline, full-text search engine for an mHealth app |
title_full_unstemmed |
Proposal of a lightweight, offline, full-text search engine for an mHealth app |
title_sort |
Proposal of a lightweight, offline, full-text search engine for an mHealth app |
author |
Carla Teixeira Lopes |
author_facet |
Carla Teixeira Lopes Azevedo, D Monteiro, JM |
author_role |
author |
author2 |
Azevedo, D Monteiro, JM |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Carla Teixeira Lopes Azevedo, D Monteiro, JM |
description |
- A patient's ability to recall and retrieve health information contributes to a better health management. HealthTalks was developed to address these issues by recording a summary of a medical appointment, uttered by the physician, and transcribing it. For each appointment, the user can also take free-text notes. Nowadays, search engines have become a ubiquitous part of everyone's life and are expected on most applications. Here, we describe the development of a search engine for HealthTalks. The app's characteristics demand a lightweight and offline engine, which requires a specific solution rather than an existing library or service. Our approach combines SQLite's Full-Text Search 4 module, which includes ngram indexing, with traditional information retrieval techniques to rank the documents. We created a test collection with summaries of clinical appointments (our documents), information needs, search queries, and relevance assessments for an initial search engine evaluation. Using this test collection, we assessed performance using NDCG@10, the first rank position of a totally relevant result, and query latency. Results are promising, with an average NDCG of 0.97. The median rank position of the first relevant result varies between 1.9 and 1.95, depending on the use of 4-gram character tokenization, an aspect that did not significantly affect the results. We expect this work to be useful for future developments of full-text search engines in mobile environments. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022 2022-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/book |
format |
book |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10216/145805 |
url |
https://hdl.handle.net/10216/145805 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.23919/cisti54924.2022.9820062 |
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.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799135628556763137 |