CALL CENTERS (CENTRES) - Faculty of Industrial Engineering and ...

Abstract. As the number and diversity of end-user environments increase, services should be
able to dynamically adapt to available resources in a given environment. We present the concepts
of migratory services and peer-to-peer connections as the means of facilitating adaptive
service and resource management in distributed and heterogeneous environments. Our approach
has been realized using object-oriented principles in an Adaptive Communicating Applications
Platform (ACAP). The architectural design and implementation of a real-life high-level service,
Virtual Call Center (VCC), are used to illustrate issues in adaptive service and management
issues and discuss in detail our approach in ACAP.
Keywords: Adaptive systems, Call centres, Distributed processing, Object-oriented methods,
Telecommunication computing, Telecommunication network management
39. Kuo, H.K.J., O. Siohan and J.P. Olive. Advances in natural language call routing, Bell Labs
Technical Journal, 7 (4), 2003, 155–170.
Abstract. The paper describes Bell Labs’ efforts in developing core technologies toward natural
language call routing (NLCR) applications. NLCR refers to technology allowing callers of a call
center to be automatically routed to their desired destination based on natural spoken responses
to an open-ended prompt, such as “How may I direct your call?”. Such services are expected to
replace interactive voice response (IVR) systems in the future, allowing a better experience for
the end user and cost savings for the call center. An NLCR system essentially combines several
key technologies, mainly automatic speech recognition (ASR) and topic identification. The role
of the ASR system is to convert the input utterance into the corresponding sequence of words.
The topic identification module then attempts to reproduce human categorization judgments in
order to route the caller to the requested destination, given the hypothesized (possibly partially
wrong) word sequence from the ASR system. The paper presents our recent advances in natural
language ASR and robust topic identification, focusing particularly on its data-driven aspect and
its portability. We also report experimental results from our field trials in the banking domain,
illustrating the maturity of the technology and its acceptance by end users, making it an enabler
of new revenue-generating services.
Keywords: Call centres, Classification, Interactive systems, Natural language interfaces, Speech
recognition, Speech-based user interfaces
40. Maass, S. Software support for interaction work in call centers. In Quality of Work and Products
in Enterprises of the Future, H. Strasser, K. Kluth, H. Rausch and H. Bubb (Eds.), Ergonomia
Verlag, Stuttgart, Germany, 2003, 975–978.
Abstract. Call centres deliver a new kind of interactive service, but present software systems
are far from adequate in supporting this. Software development seems to be based on a reduced
understanding of call centre work and neglects the social component. Detailed work analysis revealed
new software requirements. It also showed the need for revised task analysis instruments.
(Appears also in Section VII.)
41. Qiang, Yang, Wang Yong, Zhang Zhong. SANet: A service-agent network for all center scheduling,
IEEE Transactions on Systems, Man & Cybernetics, Part A: Systems & Humans, 33 (3),
135