995 resultados para Collaborative Tagging


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The purpose of this paper is to share information about the Iowa Rural HIT Collaborative efforts to help rural hospitals and providers attain electronic medical records meaningful use status. Information from this paper can be helpful to others who are pursuing solutions related to integration of health information technology in rural areas.

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Recommendation systems aim to help users make decisions more efficiently. The most widely used method in recommendation systems is collaborative filtering, of which, a critical step is to analyze a user's preferences and make recommendations of products or services based on similarity analysis with other users' ratings. However, collaborative filtering is less usable for recommendation facing the "cold start" problem, i.e. few comments being given to products or services. To tackle this problem, we propose an improved method that combines collaborative filtering and data classification. We use hotel recommendation data to test the proposed method. The accuracy of the recommendation is determined by the rankings. Evaluations regarding the accuracies of Top-3 and Top-10 recommendation lists using the 10-fold cross-validation method and ROC curves are conducted. The results show that the Top-3 hotel recommendation list proposed by the combined method has the superiority of the recommendation performance than the Top-10 list under the cold start condition in most of the times.

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Il lavoro svolto è motivato dall'esigenza di utilizzare strumenti per la gestione di grandi quantità di dati, disponibili in seguito alla diffusione del Web. Si sono analizzate le basi di conoscenza, definendone le caratteristiche comuni e presentando poi un confronto fra alcune delle più significative. Infine si è analizzato più dettagliatamente il progetto Wikidata.