Enhancing Intent Detection in Customer Service with Social Media Data
Journal
The Web Conference 2021 - Companion of the World Wide Web Conference, WWW 2021
Pages
274-275
Date Issued
2021
Author(s)
Abstract
Intent detection plays an important role in customer service dialog systems for providing high-quality service in the financial industry. The lack of publicly available datasets and high annotation cost are two challenging issues in this research direction. To overcome these challenges, we propose a social media enhanced self-Training approach for intent detection by using label names only. The experimental results show the effectiveness of the proposed method. ? 2021 ACM.
Subjects
Social networking (online); World Wide Web; Customer services; Dialog systems; Financial industry; High quality service; Intent detection; Self-training approaches; Social media; Social media datum; Service industry
Type
conference paper