Using Domain-Specific Term Frequencies to Identify and Classify Health Queries

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2013

Autores

Carla Teixeira Lopes (Autor) FEUP; Dias, D (Autor) Outra; Cristina Ribeiro (Autor) FEUP

Ata de Conferência Internacional

Título: World Conference on Information Systems and Technologies (WorldCIST)

Páginas: 221-226

Indexação

ISI Web of Knowledge - 2 Citações

Scopus - 2 Citações

Outras Informações

ID Authenticus: P-008-ACD

DOI: 10.1007/978-3-642-36981-0_21

Abstract (EN): In this paper we propose a multilingual method to identify health-related queries and classify them into health categories. Our method uses a consumer health vocabulary and the Unified Medical Language System semantic structure to compute the association degree of a query to medical concepts and categories. This method can be applied in different languages with translated versions of the health vocabulary. To evaluate its efficacy and applicability in two languages we used two manually classified sets of queries, each on a different language. Results are better for the English sample where a distance of 0.38 to the ROC optimal point (0,1) was obtained. This shows some influence of the translation in the method's performance.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6