The Internet is naturally a simple and immediate mean to retrieve information. However, not everything one can find is equally accurate and reliable. In this paper, we continue our line of research towards effective techniques for assessing the quality of online content. Focusing on the Wikipedia Medicinal Portal, in a previous work we implemented an automatic technique to assess the quality of each article and we compared our results to the classification of the articles given by the portal itself, obtaining quite different outcomes. Here, we present a lightweight instantiation of our methodology that reduces both redundant features and those not mentioned by the Wiki Project guidelines. What we obtain is a fine-grained assessment and a better discrimination of the articles’ quality, w.r.t. previous work. Our proposal could help to automatically evaluate the maturity of Wikipedia medical articles in an efficient way.
CITATION STYLE
Marzini, E., Spognardi, A., Matteucci, I., Mori, P., Petrocchi, M., & Conti, R. (2014). Improved automatic maturity assessment of wikipedia medical articles. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8841, pp. 612–622). Springer Verlag. https://doi.org/10.1007/978-3-662-45563-0_37
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