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.
Improved automatic maturity assessment of Wikipedia medical articles / Marzini, Emanuel; SPOGNARDI, Angelo; Matteucci, Ilaria; Mori, Paolo; Petrocchi, Marinella; Conti, Riccardo. - 8841:(2014), pp. 612-622. (Intervento presentato al convegno International Conferences: CoopIS and ODBASE 2014 tenutosi a Amantea; Italy).
Improved automatic maturity assessment of Wikipedia medical articles
SPOGNARDI, Angelo;
2014
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.