SuperAgent: A Customer Service Chatbot for E-commerce Websites

By Lei Cui, Shaohan Huang, Furu Wei, Chuanqi Tan, Chaoqun Duan, M. Zhou. Annual Meeting of the Association for Computational Linguistics, 2017

320 citations recorded by the source corpus.

Conventional customer service chatbots are usually based on human dialogue, yet significant issues in terms of data scale and privacy. In this paper, we present SuperAgent, a customer service chatbot that leverages large-scale and publicly available e-commerce data. Distinct from existing counterparts, SuperAgent takes advantage of data from in-page product descriptions as well as user-generated content from e-commerce websites, which is more practical and cost-effective when answering repetitive questions, freeing up human support staff to answer much higher value questions. We demonstrate SuperAgent as an add-on extension to mainstream web browsers and show its usefulness to user’s online shopping experience.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/01cec6262b3a275cfa3aca020ffba0ac2c685c56

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Zhuosheng Zhang
2. Zhao Hai
3. Meng-Han Tsai
4. Liu Yang
5. Gongshen Liu
6. Cheng Li
7. Marc Najork
8. Michael Bendersky

In Information Systems

1. Meng-Han Tsai
2. Michael Bendersky
3. Marc Najork
4. Liu Yang
5. Cheng Li
6. Mingyang Zhang
7. Zhuosheng Zhang
8. Endang Wahyu Pamungkas

Citations in the corpus

• Emotionally-Aware Chatbots: A Survey (2019, background): “Some works tried to model them into domain-specific tasks such as customer service [10, 18], and shopping assistance [22].”
• Four-Stage Framework for Implementing a Chatbot System in Disaster Emergency Operation Data Management: A Flood Disaster Management Case Study (2020, background): “For example, in the field of business, chatbot systems have been developed as the virtual assistant (Ko and Lin, 2018) and provider of customer service for e-business (Gupta et al., 2015; Thomas, 2016; Cui et al., 2017).”
• A Literature Survey of Recent Advances in Chatbots (2021, background): “[97], [98], and [99] provide different examples of chatbots applied to e-commerce.”
• Modeling Multi-turn Conversation with Deep Utterance Aggregation (2018, background): “Human-computer interactive systems are booming due to their promising potentials and alluring commercial values (Qiu et al., 2017; Cui et al., 2017; Yan et al., 2017; Huang et al., 2018; Jia and Zhao, 2014).”
• Beyond 512 Tokens: Siamese Multi-depth Transformer-based Hierarchical Encoder for Document Matching (2020, background): “Matching natural questions with similar questions or answer candidates brings us retrieval based question answering systems (e.g. Alibaba AliMe [22], Microsoft SuperAgent [4]).”