Deep Hierarchical Classification for Category Prediction in E-commerce System
Dehong Gao · 2020
In e-commerce system, category prediction is to automatically predict categories of given texts.Different from traditional classification where there are no relations between classes, category prediction is reckoned as a standard hierarchical classification problem since categories are usually organized as a hierarchical tree.In this paper, we address hierarchical category prediction.We propose a Deep Hierarchical Classification framework, which incorporates the multi-scale hierarchical information in neural networks and introduces a representation sharing strategy according to the category tree.We also define a novel combined loss function to punish hierarchical prediction losses.The evaluation shows that the proposed approach outperforms existing approaches in accuracy.