|Title:||Enhancing Intent Detection in Customer Service with Social Media Data||Authors:||Huang J
|Keywords:||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||Issue Date:||2021||Start page/Pages:||274-275||Source:||The Web Conference 2021 - Companion of the World Wide Web Conference, WWW 2021||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.
|Appears in Collections:||資訊工程學系|
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