Go to:
Logótipo
Você está em: Start > Publications > View > Comparative evaluation of web search engines in health information retrieval
Map of Premises
Principal
Publication

Comparative evaluation of web search engines in health information retrieval

Title
Comparative evaluation of web search engines in health information retrieval
Type
Article in International Scientific Journal
Year
2011
Authors
Carla Teixeira Lopes
(Author)
FEUP
View Personal Page You do not have permissions to view the institutional email. Search for Participant Publications View Authenticus page View ORCID page
Cristina Ribeiro
(Author)
FEUP
View Personal Page You do not have permissions to view the institutional email. Search for Participant Publications View Authenticus page View ORCID page
Journal
Vol. 35
Pages: 869-892
ISSN: 1468-4527
Publisher: Emerald
Other information
Authenticus ID: P-002-Z8Z
Abstract (EN): Purpose - The intent of this work is to evaluate several generalist and health-specific search engines for retrieval of health information by consumers: to compare the retrieval effectiveness of these engines for different types of clinical queries, medical specialties and condition severity; and to compare the use of evaluation metrics for binary relevance scales and for graded ones. Design/methodology/approach - The authors conducted a study in which users evaluated the relevance of documents retrieved by four search engines for two different health information needs. Users could choose between generalist (Bing, Google, Sapo and Yahoo!) and health-specific (MedlinePlus, SapoSande and WebMD) search engines. The authors then analysed the differences between search engines and groups of information needs with six different measures: graded average precision (gap), average precision (ap), gap@5, gap@10, ap@5 and ap@10. Findings The results show that generalist web search engines surpass the precision of health-specific engines. Google has the best performance, mainly in the top ten results. It was found that information needs associated with severe conditions are associated with higher precision, as are overview and psychiatry questions. Originality/value - The study is one of the first to use a recently proposed measure to evaluate the effectiveness of retrieval systems with graded relevance scales. It includes tasks from several medical specialties, types of clinical questions and different levels of severity which, to the best of the authors' knowledge, has not been clone before. Moreover, users have considerable involvement in the experiment. The results help in understanding how search engines differ in their responses to health information needs, what types of online health information are more common on the web and how to improve this type of search.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 24
Documents
We could not find any documents associated to the publication.
Related Publications

Of the same authors

Linked Cultural Heritage Data? FAIR Enough (2024)
Other Publications
Cristina Ribeiro; Inês Koch; Carla Teixeira Lopes; María Poveda Villalón; Mariano Rico
EPISA – Entity and Property Inference for Semantic Archives (2022)
Other Publications
Cristina Ribeiro; Carla Teixeira Lopes; Inês Koch; Sérgio Nunes
Data literacy and data research management: results from a Portuguese survey among researchers and academics (2017)
Summary of Presentation in an International Conference
Terra, Ana Lúcia ; Baptista, Ana Alice; Lopes, Carla Teixeira ; Ribeiro, Cristina ; Martins, Fernanda ; David, Gabriel ; Rodrigues, Irene ; Borbinha, José; Borges, Maria Manuel; Pinto, Maria Manuela Gomes de Azevedo ; Fialho, Paulo
Report on the 2nd Linked Archives International Workshop (LinkedArchives 2022) at TPDL 2022 (2022)
Article in International Scientific Journal
Carla Teixeira Lopes; Cristina Ribeiro; Niccolucci, F; Villalón, MP; Freire, N
Report on the 1st linked archives international workshop (LinkedArchives 2021) at TPDL 2021 (2021)
Article in International Scientific Journal
Carla Teixeira Lopes; Cristina Ribeiro; Niccolucci, F; Rodrigues, IP; Antunes Freire, NM

See all (32)

Of the same journal

Predicting the quality of health web documents using their characteristics (2018)
Article in International Scientific Journal
Melinda Oroszlányová; Carla Teixeira Lopes; Sérgio Nunes; Cristina Ribeiro
Recommend this page Top
Copyright 1996-2025 © Faculdade de Medicina Dentária da Universidade do Porto  I Terms and Conditions  I Acessibility  I Index A-Z
Page created on: 2025-07-16 at 05:57:38 | Privacy Policy | Personal Data Protection Policy | Whistleblowing | Electronic Yellow Book