HAEE: Question Classification Using Hierarchical Intra-Attention Enhancement Encoder

Abstract

Automated question-answering systems play an important role in e-commerce customer service systems Question classification involves assigning labels to questions according to the type of answer required Most previous approaches such as named entity recognition are based on a predefined dictionary in conjunction with machine learning to enhance accuracy In this paper we propose a hierarchical enhancement encoder featuring bidirectional gated recurrent networks and character input to address the out-of-vocabulary problem We also created multiple intra-attentions to simulate relationships among characters (in Chinese) or words (in English) to enhance the influence of tokens within a sentence In experiments conducted in a real-world corporate setting with several datasets the proposed HAEE system outperformed existing state-of-the-art models in question classification tasks particularly when applied to a Chinese corpus

Date of Award	2019
Original language	English
Supervisor	Jen-Wei Huang (Supervisor)