From Top to Down Hierarchical Classification Process with the Candidates' Strategy
Jianying Lin, Rui Liu, Quanye Jia, Yahui Zhao · 2017
While there is a large amount of text data on the Internet, people need to organize the text data with experienced category. However, the flat structure of categories could not satisfy the modern information management. To solve this problem, we propose a hierarchical classification process with a strategy, called candidates, used to relieve the blocking problems. Besides, we establish the description of categories as the supervised information to the hierarchical text classification. Extensive experiments on public corpora demonstrate our models effectiveness and efficiency.