SODA : Service Oriented Domain Adaptation Architecture for Microblog Categorization

摘要

We demonstrate SODA (Service Oriented Domain Adaptation) for efficient and scalable cross-domain microblog categorization which works on the principle of transfer learning. It is developed on a novel similarity-based iterative domain adaptation algorithm while extended with features such as active learning and interactive GUI to be used by business professionals. SODA demonstrates efficient classification accuracy on new collections while minimizing and sometimes eliminating the need for expensive data labeling efforts. SODA also implements an active learning (AL) technique to select informative instances from the new collection to seek annotations, if a small amount of labeled data is required by the adaptation algorithm.