Feb. 27, 2024, 5:41 a.m. | Shu-Ting Pi, Michael Yang, Qun Liu

cs.LG updates on arXiv.org arxiv.org

arXiv:2402.15655v1 Announce Type: new
Abstract: Customers who reach out for customer service support may face a range of issues that vary in complexity. Routing high-complexity contacts to junior agents can lead to multiple transfers or repeated contacts, while directing low-complexity contacts to senior agents can strain their capacity to assist customers who need professional help. To tackle this, a machine learning model that accurately predicts the complexity of customer issues is highly desirable. However, defining the complexity of a contact …

abstract agents arxiv capacity complexity cs.ai cs.lg customer customers customer service face junior low multiple professional routing service support type

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne