Predicting Social Annotation by Spreading Activation

Social bookmark services like del.icio.us enable easy annotation for users to organize their resources. Collaborative tagging provides useful index for information retrieval. However, lack of sufficient tags for the developing documents, in particular for new arrivals, hides important documents from being retrieved at the earlier stages. This paper proposes a spreading activation approach to predict social annotation based on document contents and users’ tagging records. Total 28,792 mature documents selected from del.icio.us are taken as answer keys. The experimental results show that this approach predicts

• Type: Conference
• Year: 2007
• Where: ICADL
• Authors: Abon Chen, Hsin-Hsi Chen, Polly Huang
• Keywords: Del.icio.us, Education, Enable Easy Annotation, ICADL 2007, Spreading Activation Approach