Abstract
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.
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Lopes, C.T., Dias, D., Ribeiro, C. (2013). Using Domain-Specific Term Frequencies to Identify and Classify Health Queries. In: Rocha, Á., Correia, A., Wilson, T., Stroetmann, K. (eds) Advances in Information Systems and Technologies. Advances in Intelligent Systems and Computing, vol 206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36981-0_21
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DOI: https://doi.org/10.1007/978-3-642-36981-0_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36980-3
Online ISBN: 978-3-642-36981-0
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