mlsanityData to 14 Oct 2026

Advising Agent for Service-Providing Live-Chat Operators

arXiv 2105.03986 ↗First posted 9 May 2021cs.CL cs.AI cs.IRcited by 1

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Abstract (arXiv)

Call centers, in which human operators attend clients using textual chat, are very common in modern e-commerce. Training enough skilled operators who are able to provide good service is a challenge. We suggest an algorithm and a method to train and implement an assisting agent that provides on-line advice to operators while they attend clients. The agent is domain-independent and can be introduced to new domains without major efforts in design, training and organizing structured knowledge of the professional discipline. We demonstrate the applicability of the system in an experiment that realizes its full life-cycle on a specific domain and analyze its capabilities.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 7 of its 63 references that are in the map. First posted on arXiv 9 May 2021.

Builds on

7 of 63 references.

References · 7

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systemscited by 35
  3. 2015A Survey of Available Corpora for Building Data-Driven Dialogue Systemscited by 33
  4. 2020Time to Transfer: Predicting and Evaluating Machine-Human Chatting Handoffcited by 7
  5. 2014Staffing Call Centers with Uncertain Arrival Rates and Co-sourcingcited by 2
  6. 2019Generating Challenge Datasets for Task-Oriented Conversational Agents through Self-Playcited by 2
  7. 2016Human-Agent Decision-making: Combining Theory and Practicecited by 1

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Citing papers per year: 2022: 1.

1 paper.