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Sobre

Sobre

Carla Teixeira Lopes é, atualmente, professora auxiliar no Departamento de Engenharia Informática da Faculdade de Engenharia da Universidade do Porto e investigadora sénior no INESC TEC. É doutorada (2013) em Engenharia Informática pela Faculdade de Engenharia da Universidade do Porto. Tem experiência de investigação e coordenação de trabalhos nas áreas de recuperação de informação, sistemas de gestão de dados, interação pessoa-computador, World Wide Web e análise de dados. A sua investigação atual está relacionada com recuperação de informação em saúde, com especial enfoque no desenvolvimento de ferramentas que apoiem os consumidores de saúde. 

 

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Carla Lopes
  • Cluster

    Informática
  • Cargo

    Investigador Sénior
  • Desde

    01 maio 2014
002
Publicações

2017

Effects of Language and Terminology of Query Suggestions on Medical Accuracy Considering Different User Characteristics

Autores
Lopes, CT; Paiva, D; Ribeiro, C;

Publicação
JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY

Abstract
Searching for health information is one of the most popular activities on the web. In this domain, users often misspell or lack knowledge of the proper medical terms to use in queries. To overcome these difficulties and attempt to retrieve higher-quality content, we developed a query suggestion system that provides alternative queries combining the Portuguese or English language with lay or medico-scientific terminology. Here we evaluate this system's impact on the medical accuracy of the knowledge acquired during the search. Evaluation shows that simply providing these suggestions contributes to reduce the quantity of incorrect content. This indicates that even when suggestions are not clicked, they are useful either for subsequent queries' formulation or for interpreting search results. Clicking on suggestions, regardless of type, leads to answers with more correct content. An analysis by type of suggestion and user characteristics showed that the benefits of certain languages and terminologies are more perceptible in users with certain levels of English proficiency and health literacy. This suggests a personalization of this suggestion system toward these characteristics. Overall, the effect of language is more preponderant than the effect of terminology. Clicks on English suggestions are clearly preferable to clicks on Portuguese ones.

2013

Measuring the value of health query translation: An analysis by user language proficiency

Autores
Lopes, CT; Ribeiro, C;

Publicação
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY

Abstract
English is by far the most used language on the web. In some domains, the existence of less content in the users' native language may not be problematic and even help to cope with the information overload. Yet, in domains such as health, where information quality is critical, a larger quantity of information may mean easier access to higher quality content. Query translation may be a good strategy to access content in other languages, but the presence of medical terms in health queries makes the translation process more difficult, even for users with very good language proficiencies. In this study, we evaluate how translating a health query affects users with different language proficiencies. We chose English as the non-native language because it is a widely spoken language and it is the most used language on the web. Our findings suggest that non-English-speaking users having at least elementary English proficiency can benefit from a system that suggests English alternatives for their queries, or automatically retrieves English content from a non-English query. This awareness of the user profile results in higher precision, more accurate medical knowledge, and better access to high-quality content. Moreover, the suggestions of English-translated queries may also trigger new health search strategies.

Teses
supervisionadas

2017

HealthTalks - Improving Health Communication and Personal Information Management

Autor
João Miguel Lopes Vale Cardoso Monteiro

Instituição
UP-FEUP

2016

HealthTranslator: automatic annotation of Web documents in order to assist health consumer’s searches

Autor
Hugo Miguel Ribeiro de Sousa

Instituição
UP-FEUP

2016

Query expansion strategies for laypeople-centred health information retrieval

Autor
Ricardo Daniel Soares da Silva

Instituição
UP-FEUP

2016

Análise de conteúdo em fóruns de saúde na Web: proposta de um esquema de classificação

Autor
Bárbara Lia Guimarães da Silva

Instituição
UP-FEUP