Provided by: Association for Computing Machinery
Date Added: Aug 2010
The authors investigate the generation of tag clouds using Bayesian models and test the hypothesis that social network information is better than overall popularity for ranking new and relevant information. They propose three tag cloud generation models based on popularity, topics and social structure. They conducted two user evaluations to compare the models for search and recommendation of music with social net-work data gathered from \"Last.fm\". Their survey shows that search with tag clouds is not practical whereas recommendation is promising.