DocTag2Vec: An Embedding Based Multi-label Learning Approach for Document Tagging
Table 2: Overall Recall on News Content Taxonomy dataset
['[EMPTY]', 'DocTag2Vec', 'DocTag2Vec (incremental)', 'Doc2Vec', 'SLEEC']
For NCT dataset, we also train the DocTag2Vec incrementally, i.e., each time we only feed 100 documents to DocTag2Vec and let it run SGD, and we keep doing so until all training samples are presented. Also, the incremental training does not sacrifice too much precision, which makes DocTag2Vec even appealing. It is not difficult to see that after b=10, adding more learners does not give significant improvement on precision. For nearest neighbor search, k′=5 would suffice.