Network-Enabled Knowledge Discovery Service Design -- Medical Online Texts

This research proposes a network-enabled knowledge discovery service design using content-based term co-occurrence network (TCN) and user-based collaborative filtering (CF) strategy to reinforce service innovation of digital content management system (CMS). Within these integrating knowledge discovery methodologies, a content-based term cooccurrence network (TCN) analysis can advance the scopes of content search management. The collaborative filtering (CF) can be used to recommend the other contents based on the similar users ratings. Using the network-enabled approach of TCN and CF, a large number of digital contents can be appropriately disseminated and recommended. In order to verify the effects of the combination's methodologies, some experiments use an online databank of online medical texts (articles) (jtami.medinform.org.tw) to demonstrate the combination of TCN and CF. To evaluate the effects of the knowledge discovery can use some testing questions through a open medical dataset (i.e., OHSUMED). Moreover, these experiments can use the evaluations of recall and precision to test and verify the effectiveness for digital content search.