@inproceedings{07f7279805cd4a128c7a928c81caa4a5,
title = "Human-in-the-loop conversation agent for customer service",
abstract = "This paper describes a prototype system for partial automation of customer service operations of a mobile telecommunications operator with a human-in-the loop conversational agent. The agent consists of an intent detection system for identifying the types of customer requests that it can handle appropriately, a slot filling information extraction system that integrates with the customer service database for a rule-based treatment of the common scenarios, and a template-based language generation system that builds response candidates that can be approved or amended by customer service operators. The main focus of this paper is on the system architecture and machine learning system structure design, and the observations of a limited pilot study performed to evaluate the proposed system on customer messages in Latvian. We also discuss the business requirements and practical application limitations and their influence on the design of the natural language processing components.",
keywords = "Conversational agents, Intent detection, NER",
author = "Pēteris Paikens and Artūrs Znotiņ{\v s} and Guntis Bārzdiņ{\v s}",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.",
year = "2020",
doi = "10.1007/978-3-030-51310-8\_25",
language = "English",
isbn = "9783030513092",
volume = "12089 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "277--284",
editor = "Elisabeth M{\'e}tais and Farid Meziane and Helmut Horacek and Philipp Cimiano",
booktitle = "Natural Language Processing and Information Systems - 25th International Conference on Applications of Natural Language to Information Systems, NLDB 2020, Proceedings",
}