Encoder-Decoder Neural Networks for Taxonomy Classification

This paper describes our taxonomy classifier for SIGIR eComRakuten Data Challenge.We propose a taxonomy classifier based on sequenceto-sequence neural networks, which are widely used in machine translation and automatic document summarization, by treating taxonomy classification as the translation problem from a description of a product to a category path. Experiments show that our method can predict category paths more accurately than baseline classifier. CCS CONCEPTS • Computing methodologies→ Information extraction;