| 摘要 |
Systems and methods that analyze aggregated tagging behavior of users, and evaluate such tagging trends to identify criteria for taxonomy applications. Initially, existence of a possible trend of tagging data based on collective user behavior is determined. Subsequently, tagging trends can be examined to identify that a predetermined convergence criteria has in fact been met, and/or establish such criteria for taxonomy applications. Machine learning systems (implicitly as well as explicitly trained) can be supplied to facilitate determining the trends and the convergence criteria.
|
