Modeling Conversational Agents for Service Systems

Service providers are increasingly exploring the use of conversational agents (CA) or dialogue based systems to support end customers, as a CA promises natural method for users to interact and a convenient channel for customer service. Commercial CAs, excel in addressing specific tasks or functions such as searching for restaurants, providing location directions, or scheduling meetings, with small variations in the user request. Designing a CA for a more complex service system, requires sufficient knowledge of its services such as the service capabilities, their constraints, and effects, in addition to understanding user utterances. The design of a CA is typically an independent activity and its linkages to the service system it supports are left to the designers. In this paper, we study existing work with respect to text-based CAs and identify the conceptual elements of a CA. Further, a linkage between the model elements of a CA and service model of the service system it supports is established and presented. We show that interesting insights can be derived from the linkages, that can be useful to CA designers.

[1]  Xiang Zhang,et al.  Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems , 2015, ICLR.

[2]  Geoffrey Zweig,et al.  Using Recurrent Neural Networks for Slot Filling in Spoken Language Understanding , 2015, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[3]  Shazia Afzal,et al.  Development and Deployment of a Large-Scale Dialog-based Intelligent Tutoring System , 2019, NAACL.

[4]  C. Nass,et al.  Machines and Mindlessness , 2000 .

[5]  Jason Weston,et al.  Learning End-to-End Goal-Oriented Dialog , 2016, ICLR.

[6]  Paul P. Maglio,et al.  The service system is the basic abstraction of service science , 2009, Inf. Syst. E Bus. Manag..

[7]  Jorge S. Cardoso,et al.  Evolution and Overview of Linked USDL , 2015, IESS.

[8]  Alexander Maedche,et al.  Towards Designing Cooperative and Social Conversational Agents for Customer Service , 2017, ICIS.

[9]  Jordi Cabot,et al.  Multi-platform Chatbot Modeling and Deployment with the Jarvis Framework , 2019, CAiSE.

[10]  Stefan Ultes,et al.  MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling , 2018, EMNLP.

[11]  Hui Xiong,et al.  Semantics-Based Automated Service Discovery , 2012, IEEE Transactions on Services Computing.

[12]  Daniel Oberle,et al.  Design Overview of USDL , 2012, Handbook of Service Description.

[13]  Dilek Z. Hakkani-Tür,et al.  End-to-end joint learning of natural language understanding and dialogue manager , 2016, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[14]  Dongho Kim,et al.  POMDP-based dialogue manager adaptation to extended domains , 2013, SIGDIAL Conference.

[15]  Siobhan Chapman.  Logic and Conversation , 2005 .